diff --git a/.github/workflows/new_problem_check.yml b/.github/workflows/new_problem_check.yml
new file mode 100644
index 0000000..5a13ee6
--- /dev/null
+++ b/.github/workflows/new_problem_check.yml
@@ -0,0 +1,37 @@
+name: New Problem Check
+
+on:
+  push:
+    paths:
+      - "utils/new_problem.yaml"
+  pull_request:
+    paths:
+      - "utils/new_problem.yaml"
+  workflow_dispatch: # allow triggering workflow manually
+    inputs:
+      reason:
+        description: "Reason for Running"
+        required: false
+        default: "Manually trigger problem check"
+
+jobs:
+  check_new_problems:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v3
+
+      - name: Set up Python
+        uses: actions/setup-python@v4
+        with:
+          python-version: '3.x'
+
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install -r utils/requirements.txt
+
+      - name: Run New Problem Check
+        run: |
+          python utils/validate_yaml.py utils/new_problem.yaml
+
diff --git a/.gitignore b/.gitignore
index f7275bb..e15106e 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1 +1,216 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[codz]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#   Usually these files are written by a python script from a template
+#   before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py.cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+# Pipfile.lock
+
+# UV
+#   Similar to Pipfile.lock, it is generally recommended to include uv.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+# uv.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+# poetry.lock
+# poetry.toml
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#   pdm recommends including project-wide configuration in pdm.toml, but excluding .pdm-python.
+#   https://pdm-project.org/en/latest/usage/project/#working-with-version-control
+# pdm.lock
+# pdm.toml
+.pdm-python
+.pdm-build/
+
+# pixi
+#   Similar to Pipfile.lock, it is generally recommended to include pixi.lock in version control.
+# pixi.lock
+#   Pixi creates a virtual environment in the .pixi directory, just like venv module creates one
+#   in the .venv directory. It is recommended not to include this directory in version control.
+.pixi
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# Redis
+*.rdb
+*.aof
+*.pid
+
+# RabbitMQ
+mnesia/
+rabbitmq/
+rabbitmq-data/
+
+# ActiveMQ
+activemq-data/
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.envrc
+.venv
+env/
 venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#   JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#   be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#   and can be added to the global gitignore or merged into this file.  For a more nuclear
+#   option (not recommended) you can uncomment the following to ignore the entire idea folder.
+# .idea/
+
+# Abstra
+#   Abstra is an AI-powered process automation framework.
+#   Ignore directories containing user credentials, local state, and settings.
+#   Learn more at https://abstra.io/docs
+.abstra/
+
+# Visual Studio Code
+#   Visual Studio Code specific template is maintained in a separate VisualStudioCode.gitignore 
+#   that can be found at https://github.com/github/gitignore/blob/main/Global/VisualStudioCode.gitignore
+#   and can be added to the global gitignore or merged into this file. However, if you prefer, 
+#   you could uncomment the following to ignore the entire vscode folder
+# .vscode/
+
+# Ruff stuff:
+.ruff_cache/
+
+# PyPI configuration file
+.pypirc
+
+# Marimo
+marimo/_static/
+marimo/_lsp/
+__marimo__/
+
+# Streamlit
+.streamlit/secrets.toml
diff --git a/README.md b/README.md
index 6f37f53..24de4d3 100644
--- a/README.md
+++ b/README.md
@@ -2,7 +2,9 @@
 Collection of optimisation problems and benchmark suites with information about high level properties like the type of decision variables, number of objectives, and the presence of constraints. Where available references to papers describing the problem and implementations are included.
 
 ## Contributing
-Contributions and corrections are very welcome, through pull requests, issue reporting, or email.
+Contributions and corrections are very welcome, through pull requests, issue reporting, or email. 
+
+If you want to provide a problem/suite/generator, you can also do so via this [form](https://docs.google.com/forms/d/e/1FAIpQLSehQp24AuFAH2j9jizDhq8K_BYgNGMKXWTMu6s-2RwEJrK59Q/viewform?usp=sharing&ouid=107462254722022409950).
 
 ### Details to provide
 It is often far easier for the creator of a problem/suite/generator, or someone working with it, to provide details about it than for someone new to it. Currently, the following specific details are being collected:
diff --git a/docs/header.html b/docs/header.html
index 5d1adbe..62df510 100644
--- a/docs/header.html
+++ b/docs/header.html
@@ -22,5 +22,5 @@
 <h2>OPL &ndash; Optimisation problem library</h2>
 
 <p>
-Submit problems and corrections on <a target="_blank" href="https://github.com/OpenOptimizationOrg/OPL/">GitHub</a> with pull requests / issues, or by email: <a href="mailto:koen.van.der.blom@cwi.nl" itemprop="email">koen.van.der.blom@cwi.nl</a>
+Submit problems and corrections on <a target="_blank" href="https://github.com/OpenOptimizationOrg/OPL/">GitHub</a> with pull requests / issues, through the <a target="_blank" href="https://docs.google.com/forms/d/e/1FAIpQLSehQp24AuFAH2j9jizDhq8K_BYgNGMKXWTMu6s-2RwEJrK59Q/viewform">Google form</a>, or by email: <a href="mailto:koen.van.der.blom@cwi.nl" itemprop="email">koen.van.der.blom@cwi.nl</a>
 </p>
diff --git a/docs/index.html b/docs/index.html
index ad3eef9..c3a5882 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -22,7 +22,7 @@
 <h2>OPL &ndash; Optimisation problem library</h2>
 
 <p>
-Submit problems and corrections on <a target="_blank" href="https://github.com/OpenOptimizationOrg/OPL/">GitHub</a> with pull requests / issues, or by email: <a href="mailto:koen.van.der.blom@cwi.nl" itemprop="email">koen.van.der.blom@cwi.nl</a>
+Submit problems and corrections on <a target="_blank" href="https://github.com/OpenOptimizationOrg/OPL/">GitHub</a> with pull requests / issues, through the <a target="_blank" href="https://docs.google.com/forms/d/e/1FAIpQLSehQp24AuFAH2j9jizDhq8K_BYgNGMKXWTMu6s-2RwEJrK59Q/viewform">Google form</a>, or by email: <a href="mailto:koen.van.der.blom@cwi.nl" itemprop="email">koen.van.der.blom@cwi.nl</a>
 </p>
 <table class="dataframe display compact display styled-table" id="problems">
   <thead>
@@ -55,8 +55,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1080/10556788.2020.1808977" target="_blank">https://doi.org/10.1080/10556788.2020.1808977</a></td>
-      <td><a href="https://github.com/numbbo/coco" target="_blank">https://github.com/numbbo/coco</a></td>
+      <td><a href="https://doi.org/10.1080/10556788.2020.1808977">https://doi.org/10.1080/10556788.2020.1808977</a></td>
+      <td><a href="https://github.com/numbbo/coco">https://github.com/numbbo/coco</a></td>
     </tr>
     <tr>
       <td>BBOB-biobj</td>
@@ -70,8 +70,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.48550/arXiv.1604.00359" target="_blank">https://doi.org/10.48550/arXiv.1604.00359</a></td>
-      <td><a href="https://github.com/numbbo/coco" target="_blank">https://github.com/numbbo/coco</a></td>
+      <td><a href="https://doi.org/10.48550/arXiv.1604.00359">https://doi.org/10.48550/arXiv.1604.00359</a></td>
+      <td><a href="https://github.com/numbbo/coco">https://github.com/numbbo/coco</a></td>
     </tr>
     <tr>
       <td>BBOB-noisy</td>
@@ -85,8 +85,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>yes</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://hal.inria.fr/inria-00369466" target="_blank">https://hal.inria.fr/inria-00369466</a></td>
-      <td><a href="https://web.archive.org/web/20210416065610/https://coco.gforge.inria.fr/doku.php?id=downloads" target="_blank">https://web.archive.org/web/20210416065610/https://coco.gforge.inria.fr/doku.php?id=downloads</a></td>
+      <td><a href="https://hal.inria.fr/inria-00369466">https://hal.inria.fr/inria-00369466</a></td>
+      <td><a href="https://web.archive.org/web/20210416065610/https://coco.gforge.inria.fr/doku.php?id=downloads">https://web.archive.org/web/20210416065610/https://coco.gforge.inria.fr/doku.php?id=downloads</a></td>
     </tr>
     <tr>
       <td>BBOB-largescale</td>
@@ -100,8 +100,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.48550/arXiv.1903.06396" target="_blank">https://doi.org/10.48550/arXiv.1903.06396</a></td>
-      <td><a href="https://github.com/numbbo/coco" target="_blank">https://github.com/numbbo/coco</a></td>
+      <td><a href="https://doi.org/10.48550/arXiv.1903.06396">https://doi.org/10.48550/arXiv.1903.06396</a></td>
+      <td><a href="https://github.com/numbbo/coco">https://github.com/numbbo/coco</a></td>
     </tr>
     <tr>
       <td>BBOB-mixint</td>
@@ -115,8 +115,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1145/3321707.3321868" target="_blank">https://doi.org/10.1145/3321707.3321868</a></td>
-      <td><a href="https://github.com/numbbo/coco" target="_blank">https://github.com/numbbo/coco</a></td>
+      <td><a href="https://doi.org/10.1145/3321707.3321868">https://doi.org/10.1145/3321707.3321868</a></td>
+      <td><a href="https://github.com/numbbo/coco">https://github.com/numbbo/coco</a></td>
     </tr>
     <tr>
       <td>BBOB-biobj-mixint</td>
@@ -130,8 +130,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1145/3321707.3321868" target="_blank">https://doi.org/10.1145/3321707.3321868</a></td>
-      <td><a href="https://github.com/numbbo/coco" target="_blank">https://github.com/numbbo/coco</a></td>
+      <td><a href="https://doi.org/10.1145/3321707.3321868">https://doi.org/10.1145/3321707.3321868</a></td>
+      <td><a href="https://github.com/numbbo/coco">https://github.com/numbbo/coco</a></td>
     </tr>
     <tr>
       <td>BBOB-constrained</td>
@@ -145,8 +145,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="http://numbbo.github.io/coco-doc/bbob-constrained/" target="_blank">http://numbbo.github.io/coco-doc/bbob-constrained/</a></td>
-      <td><a href="https://github.com/numbbo/coco" target="_blank">https://github.com/numbbo/coco</a></td>
+      <td><a href="http://numbbo.github.io/coco-doc/bbob-constrained/">http://numbbo.github.io/coco-doc/bbob-constrained/</a></td>
+      <td><a href="https://github.com/numbbo/coco">https://github.com/numbbo/coco</a></td>
     </tr>
     <tr>
       <td>MOrepo</td>
@@ -161,7 +161,7 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td></td>
       <td></td>
-      <td><a href="https://github.com/MCDMSociety/MOrepo" target="_blank">https://github.com/MCDMSociety/MOrepo</a></td>
+      <td><a href="https://github.com/MCDMSociety/MOrepo">https://github.com/MCDMSociety/MOrepo</a></td>
     </tr>
     <tr>
       <td>ZDT</td>
@@ -175,8 +175,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1162/106365600568202" target="_blank">https://doi.org/10.1162/106365600568202</a></td>
-      <td><a href="https://github.com/anyoptimization/pymoo" target="_blank">https://github.com/anyoptimization/pymoo</a></td>
+      <td><a href="https://doi.org/10.1162/106365600568202">https://doi.org/10.1162/106365600568202</a></td>
+      <td><a href="https://github.com/anyoptimization/pymoo">https://github.com/anyoptimization/pymoo</a></td>
     </tr>
     <tr>
       <td>DTLZ</td>
@@ -190,8 +190,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1109/CEC.2002.1007032" target="_blank">https://doi.org/10.1109/CEC.2002.1007032</a></td>
-      <td><a href="https://pymoo.org/problems/many/dtlz.html" target="_blank">https://pymoo.org/problems/many/dtlz.html</a></td>
+      <td><a href="https://doi.org/10.1109/CEC.2002.1007032">https://doi.org/10.1109/CEC.2002.1007032</a></td>
+      <td><a href="https://pymoo.org/problems/many/dtlz.html">https://pymoo.org/problems/many/dtlz.html</a></td>
     </tr>
     <tr>
       <td>WFG</td>
@@ -205,8 +205,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1109/TEVC.2005.861417" target="_blank">https://doi.org/10.1109/TEVC.2005.861417</a></td>
-      <td><a href="https://pymoo.org/problems/many/wfg.html" target="_blank">https://pymoo.org/problems/many/wfg.html</a></td>
+      <td><a href="https://doi.org/10.1109/TEVC.2005.861417">https://doi.org/10.1109/TEVC.2005.861417</a></td>
+      <td><a href="https://pymoo.org/problems/many/wfg.html">https://pymoo.org/problems/many/wfg.html</a></td>
     </tr>
     <tr>
       <td>CDMP</td>
@@ -220,7 +220,7 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>?</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1145/3321707.3321878" target="_blank">https://doi.org/10.1145/3321707.3321878</a></td>
+      <td><a href="https://doi.org/10.1145/3321707.3321878">https://doi.org/10.1145/3321707.3321878</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -235,7 +235,7 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>?</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1109/TCYB.2019.2896021" target="_blank">https://doi.org/10.1109/TCYB.2019.2896021</a></td>
+      <td><a href="https://doi.org/10.1109/TCYB.2019.2896021">https://doi.org/10.1109/TCYB.2019.2896021</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -250,7 +250,7 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>?</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1016/j.swevo.2019.02.003" target="_blank">https://doi.org/10.1016/j.swevo.2019.02.003</a></td>
+      <td><a href="https://doi.org/10.1016/j.swevo.2019.02.003">https://doi.org/10.1016/j.swevo.2019.02.003</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -265,7 +265,7 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>?</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1109/CEC.2019.8790277" target="_blank">https://doi.org/10.1109/CEC.2019.8790277</a></td>
+      <td><a href="https://doi.org/10.1109/CEC.2019.8790277">https://doi.org/10.1109/CEC.2019.8790277</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -280,7 +280,7 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>optional</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1016/j.asoc.2020.106139" target="_blank">https://doi.org/10.1016/j.asoc.2020.106139</a></td>
+      <td><a href="https://doi.org/10.1016/j.asoc.2020.106139">https://doi.org/10.1016/j.asoc.2020.106139</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -295,8 +295,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.48550/arXiv.2110.08033" target="_blank">https://doi.org/10.48550/arXiv.2110.08033</a></td>
-      <td><a href="https://github.com/songbai-liu/etmo" target="_blank">https://github.com/songbai-liu/etmo</a></td>
+      <td><a href="https://doi.org/10.48550/arXiv.2110.08033">https://doi.org/10.48550/arXiv.2110.08033</a></td>
+      <td><a href="https://github.com/songbai-liu/etmo">https://github.com/songbai-liu/etmo</a></td>
     </tr>
     <tr>
       <td>MMOPP</td>
@@ -310,8 +310,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="http://www5.zzu.edu.cn/system/_content/download.jsp?urltype=news.DownloadAttachUrl&owner=1327567121&wbfileid=4764412" target="_blank">http://www5.zzu.edu.cn/system/_content/download.jsp?urltype=news.DownloadAttachUrl&amp;owner=1327567121&amp;wbfileid=4764412</a></td>
-      <td><a href="http://www5.zzu.edu.cn/ecilab/info/1036/1251.htm" target="_blank">http://www5.zzu.edu.cn/ecilab/info/1036/1251.htm</a></td>
+      <td><a href="http://www5.zzu.edu.cn/system/_content/download.jsp?urltype=news.DownloadAttachUrl&owner=1327567121&wbfileid=4764412">http://www5.zzu.edu.cn/system/_content/download.jsp?urltype=news.DownloadAttachUrl&owner=1327567121&wbfileid=4764412</a></td>
+      <td><a href="http://www5.zzu.edu.cn/ecilab/info/1036/1251.htm">http://www5.zzu.edu.cn/ecilab/info/1036/1251.htm</a></td>
     </tr>
     <tr>
       <td>CFD</td>
@@ -325,8 +325,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td>real world</td>
-      <td><a href="https://doi.org/10.1007/978-3-319-99259-4_24" target="_blank">https://doi.org/10.1007/978-3-319-99259-4_24</a></td>
-      <td><a href="https://bitbucket.org/arahat/cfd-test-problem-suite" target="_blank">https://bitbucket.org/arahat/cfd-test-problem-suite</a></td>
+      <td><a href="https://doi.org/10.1007/978-3-319-99259-4_24">https://doi.org/10.1007/978-3-319-99259-4_24</a></td>
+      <td><a href="https://bitbucket.org/arahat/cfd-test-problem-suite">https://bitbucket.org/arahat/cfd-test-problem-suite</a></td>
     </tr>
     <tr>
       <td>GBEA</td>
@@ -340,7 +340,7 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>yes</td>
       <td>no</td>
       <td>real world</td>
-      <td><a href="https://doi.org/10.1145/3321707.3321805" target="_blank">https://doi.org/10.1145/3321707.3321805</a></td>
+      <td><a href="https://doi.org/10.1145/3321707.3321805">https://doi.org/10.1145/3321707.3321805</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -355,8 +355,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td>real world</td>
-      <td><a href="https://doi.org/10.1145/3205651.3205702" target="_blank">https://doi.org/10.1145/3205651.3205702</a></td>
-      <td><a href="http://ladse.eng.isas.jaxa.jp/benchmark/" target="_blank">http://ladse.eng.isas.jaxa.jp/benchmark/</a></td>
+      <td><a href="https://doi.org/10.1145/3205651.3205702">https://doi.org/10.1145/3205651.3205702</a></td>
+      <td><a href="http://ladse.eng.isas.jaxa.jp/benchmark/">http://ladse.eng.isas.jaxa.jp/benchmark/</a></td>
     </tr>
     <tr>
       <td>EMO2017</td>
@@ -370,8 +370,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td>real world</td>
-      <td><a href="https://www.ini.rub.de/PEOPLE/glasmtbl/projects/bbcomp/" target="_blank">https://www.ini.rub.de/PEOPLE/glasmtbl/projects/bbcomp/</a></td>
-      <td><a href="https://www.ini.rub.de/PEOPLE/glasmtbl/projects/bbcomp/downloads/realworld-problems-bbcomp-EMO-2017.zip" target="_blank">https://www.ini.rub.de/PEOPLE/glasmtbl/projects/bbcomp/downloads/realworld-problems-bbcomp-EMO-2017.zip</a></td>
+      <td><a href="https://www.ini.rub.de/PEOPLE/glasmtbl/projects/bbcomp/">https://www.ini.rub.de/PEOPLE/glasmtbl/projects/bbcomp/</a></td>
+      <td><a href="https://www.ini.rub.de/PEOPLE/glasmtbl/projects/bbcomp/downloads/realworld-problems-bbcomp-EMO-2017.zip">https://www.ini.rub.de/PEOPLE/glasmtbl/projects/bbcomp/downloads/realworld-problems-bbcomp-EMO-2017.zip</a></td>
     </tr>
     <tr>
       <td>JSEC2019</td>
@@ -385,8 +385,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td>real world</td>
-      <td><a href="http://www.jpnsec.org/files/competition2019/EC-Symposium-2019-Competition-English.html" target="_blank">http://www.jpnsec.org/files/competition2019/EC-Symposium-2019-Competition-English.html</a></td>
-      <td><a href="http://www.jpnsec.org/files/competition2019/EC-Symposium-2019-Competition-English.html" target="_blank">http://www.jpnsec.org/files/competition2019/EC-Symposium-2019-Competition-English.html</a></td>
+      <td><a href="http://www.jpnsec.org/files/competition2019/EC-Symposium-2019-Competition-English.html">http://www.jpnsec.org/files/competition2019/EC-Symposium-2019-Competition-English.html</a></td>
+      <td><a href="http://www.jpnsec.org/files/competition2019/EC-Symposium-2019-Competition-English.html">http://www.jpnsec.org/files/competition2019/EC-Symposium-2019-Competition-English.html</a></td>
     </tr>
     <tr>
       <td>RE</td>
@@ -400,8 +400,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td>real world like</td>
-      <td><a href="https://doi.org/10.1016/j.asoc.2020.106078" target="_blank">https://doi.org/10.1016/j.asoc.2020.106078</a></td>
-      <td><a href="https://github.com/ryojitanabe/reproblems" target="_blank">https://github.com/ryojitanabe/reproblems</a></td>
+      <td><a href="https://doi.org/10.1016/j.asoc.2020.106078">https://doi.org/10.1016/j.asoc.2020.106078</a></td>
+      <td><a href="https://github.com/ryojitanabe/reproblems">https://github.com/ryojitanabe/reproblems</a></td>
     </tr>
     <tr>
       <td>CRE</td>
@@ -415,8 +415,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td>real world like</td>
-      <td><a href="https://doi.org/10.1016/j.asoc.2020.106078" target="_blank">https://doi.org/10.1016/j.asoc.2020.106078</a></td>
-      <td><a href="https://github.com/ryojitanabe/reproblems" target="_blank">https://github.com/ryojitanabe/reproblems</a></td>
+      <td><a href="https://doi.org/10.1016/j.asoc.2020.106078">https://doi.org/10.1016/j.asoc.2020.106078</a></td>
+      <td><a href="https://github.com/ryojitanabe/reproblems">https://github.com/ryojitanabe/reproblems</a></td>
     </tr>
     <tr>
       <td>Radar waveform</td>
@@ -430,8 +430,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td>real world</td>
-      <td><a href="https://doi.org/10.1007/978-3-540-70928-2_53" target="_blank">https://doi.org/10.1007/978-3-540-70928-2_53</a></td>
-      <td><a href="http://code.evanhughes.org/" target="_blank">http://code.evanhughes.org/</a></td>
+      <td><a href="https://doi.org/10.1007/978-3-540-70928-2_53">https://doi.org/10.1007/978-3-540-70928-2_53</a></td>
+      <td><a href="http://code.evanhughes.org/">http://code.evanhughes.org/</a></td>
     </tr>
     <tr>
       <td>MF2</td>
@@ -445,8 +445,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>yes</td>
       <td></td>
-      <td><a href="https://doi.org/10.21105/joss.02049" target="_blank">https://doi.org/10.21105/joss.02049</a></td>
-      <td><a href="https://github.com/sjvrijn/mf2" target="_blank">https://github.com/sjvrijn/mf2</a></td>
+      <td><a href="https://doi.org/10.21105/joss.02049">https://doi.org/10.21105/joss.02049</a></td>
+      <td><a href="https://github.com/sjvrijn/mf2">https://github.com/sjvrijn/mf2</a></td>
     </tr>
     <tr>
       <td>AMVOP</td>
@@ -460,7 +460,7 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1109/TEVC.2013.2281531" target="_blank">https://doi.org/10.1109/TEVC.2013.2281531</a></td>
+      <td><a href="https://doi.org/10.1109/TEVC.2013.2281531">https://doi.org/10.1109/TEVC.2013.2281531</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -475,7 +475,7 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td>real world</td>
-      <td><a href="https://doi.org/10.1109/TEVC.2013.2281531" target="_blank">https://doi.org/10.1109/TEVC.2013.2281531</a></td>
+      <td><a href="https://doi.org/10.1109/TEVC.2013.2281531">https://doi.org/10.1109/TEVC.2013.2281531</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -490,8 +490,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.48550/arXiv.2305.12221" target="_blank">https://doi.org/10.48550/arXiv.2305.12221</a></td>
-      <td><a href="https://github.com/IOHprofiler/IOHexperimenter/" target="_blank">https://github.com/IOHprofiler/IOHexperimenter/</a></td>
+      <td><a href="https://doi.org/10.48550/arXiv.2305.12221">https://doi.org/10.48550/arXiv.2305.12221</a></td>
+      <td><a href="https://github.com/IOHprofiler/IOHexperimenter/">https://github.com/IOHprofiler/IOHexperimenter/</a></td>
     </tr>
     <tr>
       <td>ρMNK-Landscapes</td>
@@ -505,8 +505,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1016/j.ejor.2012.12.019" target="_blank">https://doi.org/10.1016/j.ejor.2012.12.019</a></td>
-      <td><a href="https://gitlab.com/aliefooghe/mocobench/" target="_blank">https://gitlab.com/aliefooghe/mocobench/</a></td>
+      <td><a href="https://doi.org/10.1016/j.ejor.2012.12.019">https://doi.org/10.1016/j.ejor.2012.12.019</a></td>
+      <td><a href="https://gitlab.com/aliefooghe/mocobench/">https://gitlab.com/aliefooghe/mocobench/</a></td>
     </tr>
     <tr>
       <td>mUBQP</td>
@@ -520,8 +520,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1016/j.asoc.2013.11.008" target="_blank">https://doi.org/10.1016/j.asoc.2013.11.008</a></td>
-      <td><a href="https://gitlab.com/aliefooghe/mocobench/" target="_blank">https://gitlab.com/aliefooghe/mocobench/</a></td>
+      <td><a href="https://doi.org/10.1016/j.asoc.2013.11.008">https://doi.org/10.1016/j.asoc.2013.11.008</a></td>
+      <td><a href="https://gitlab.com/aliefooghe/mocobench/">https://gitlab.com/aliefooghe/mocobench/</a></td>
     </tr>
     <tr>
       <td>ρmTSP</td>
@@ -535,8 +535,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1007/978-3-319-45823-6_40" target="_blank">https://doi.org/10.1007/978-3-319-45823-6_40</a></td>
-      <td><a href="https://gitlab.com/aliefooghe/mocobench/" target="_blank">https://gitlab.com/aliefooghe/mocobench/</a></td>
+      <td><a href="https://doi.org/10.1007/978-3-319-45823-6_40">https://doi.org/10.1007/978-3-319-45823-6_40</a></td>
+      <td><a href="https://gitlab.com/aliefooghe/mocobench/">https://gitlab.com/aliefooghe/mocobench/</a></td>
     </tr>
     <tr>
       <td>CEC2015-DMOO</td>
@@ -565,8 +565,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>optional</td>
       <td>Real-world-like</td>
-      <td><a href="https://doi.org/10.1145/3638530.3654299" target="_blank">https://doi.org/10.1145/3638530.3654299</a></td>
-      <td><a href="https://github.com/qrenau/Ealain" target="_blank">https://github.com/qrenau/Ealain</a></td>
+      <td><a href="https://doi.org/10.1145/3638530.3654299">https://doi.org/10.1145/3638530.3654299</a></td>
+      <td><a href="https://github.com/qrenau/Ealain">https://github.com/qrenau/Ealain</a></td>
     </tr>
     <tr>
       <td>MA-BBOB</td>
@@ -580,8 +580,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td>artificial</td>
-      <td><a href="https://doi.org/10.1145/3673908" target="_blank">https://doi.org/10.1145/3673908</a></td>
-      <td><a href="https://github.com/IOHprofiler/IOHexperimenter/blob/master/example/Competitions/MA-BBOB/Example_MABBOB.ipynb" target="_blank">https://github.com/IOHprofiler/IOHexperimenter/blob/master/example/Competitions/MA-BBOB/Example_MABBOB.ipynb</a></td>
+      <td><a href="https://doi.org/10.1145/3673908">https://doi.org/10.1145/3673908</a></td>
+      <td><a href="https://github.com/IOHprofiler/IOHexperimenter/blob/master/example/Competitions/MA-BBOB/Example_MABBOB.ipynb">https://github.com/IOHprofiler/IOHexperimenter/blob/master/example/Competitions/MA-BBOB/Example_MABBOB.ipynb</a></td>
     </tr>
     <tr>
       <td>MPM2</td>
@@ -595,8 +595,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://ls11-www.cs.tu-dortmund.de/_media/techreports/tr15-01.pdf" target="_blank">https://ls11-www.cs.tu-dortmund.de/_media/techreports/tr15-01.pdf</a></td>
-      <td><a href="https://github.com/jakobbossek/smoof/blob/master/inst/mpm2.py" target="_blank">https://github.com/jakobbossek/smoof/blob/master/inst/mpm2.py</a></td>
+      <td><a href="https://ls11-www.cs.tu-dortmund.de/_media/techreports/tr15-01.pdf">https://ls11-www.cs.tu-dortmund.de/_media/techreports/tr15-01.pdf</a></td>
+      <td><a href="https://github.com/jakobbossek/smoof/blob/master/inst/mpm2.py">https://github.com/jakobbossek/smoof/blob/master/inst/mpm2.py</a></td>
     </tr>
     <tr>
       <td>Convex DTLZ2</td>
@@ -610,7 +610,7 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1109/TEVC.2013.2281535" target="_blank">https://doi.org/10.1109/TEVC.2013.2281535</a></td>
+      <td><a href="https://doi.org/10.1109/TEVC.2013.2281535">https://doi.org/10.1109/TEVC.2013.2281535</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -625,7 +625,7 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1109/TEVC.2013.2281534" target="_blank">https://doi.org/10.1109/TEVC.2013.2281534</a></td>
+      <td><a href="https://doi.org/10.1109/TEVC.2013.2281534">https://doi.org/10.1109/TEVC.2013.2281534</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -640,7 +640,7 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1109/TEVC.2016.2587749" target="_blank">https://doi.org/10.1109/TEVC.2016.2587749</a></td>
+      <td><a href="https://doi.org/10.1109/TEVC.2016.2587749">https://doi.org/10.1109/TEVC.2016.2587749</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -655,7 +655,7 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1109/TEVC.2016.2587749" target="_blank">https://doi.org/10.1109/TEVC.2016.2587749</a></td>
+      <td><a href="https://doi.org/10.1109/TEVC.2016.2587749">https://doi.org/10.1109/TEVC.2016.2587749</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -670,7 +670,7 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1145/1143997.1144179" target="_blank">https://doi.org/10.1145/1143997.1144179</a></td>
+      <td><a href="https://doi.org/10.1145/1143997.1144179">https://doi.org/10.1145/1143997.1144179</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -685,7 +685,7 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1145/1143997.1144179" target="_blank">https://doi.org/10.1145/1143997.1144179</a></td>
+      <td><a href="https://doi.org/10.1145/1143997.1144179">https://doi.org/10.1145/1143997.1144179</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -700,7 +700,7 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1145/1143997.1144179" target="_blank">https://doi.org/10.1145/1143997.1144179</a></td>
+      <td><a href="https://doi.org/10.1145/1143997.1144179">https://doi.org/10.1145/1143997.1144179</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -715,7 +715,7 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1145/1143997.1144179" target="_blank">https://doi.org/10.1145/1143997.1144179</a></td>
+      <td><a href="https://doi.org/10.1145/1143997.1144179">https://doi.org/10.1145/1143997.1144179</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -730,7 +730,7 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1145/1143997.1144179" target="_blank">https://doi.org/10.1145/1143997.1144179</a></td>
+      <td><a href="https://doi.org/10.1145/1143997.1144179">https://doi.org/10.1145/1143997.1144179</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -745,12 +745,12 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td>artificial</td>
-      <td><a href="https://www.academia.edu/download/94499025/TR-CEC2018-DMOP-Competition.pdf" target="_blank">https://www.academia.edu/download/94499025/TR-CEC2018-DMOP-Competition.pdf</a></td>
-      <td><a href="https://pymoo.org/problems/dynamic/df.html" target="_blank">https://pymoo.org/problems/dynamic/df.html</a></td>
+      <td><a href="https://www.academia.edu/download/94499025/TR-CEC2018-DMOP-Competition.pdf">https://www.academia.edu/download/94499025/TR-CEC2018-DMOP-Competition.pdf</a></td>
+      <td><a href="https://pymoo.org/problems/dynamic/df.html">https://pymoo.org/problems/dynamic/df.html</a></td>
     </tr>
     <tr>
       <td>MODAct - multiobjective design of actuators</td>
-      <td>Realistic Constrained Multi-Objective Optimization Benchmark Problems from Design. Need the https://github.com/epfl-lamd/modact package installed; evaluation times around 20ms</td>
+      <td>Realistic Constrained Multi-Objective Optimization Benchmark Problems from Design. Need the <a href="https://github.com/epfl-lamd/modact">https://github.com/epfl-lamd/modact</a> package installed; evaluation times around 20ms</td>
       <td>suite</td>
       <td>2 3 4 or 5</td>
       <td>20</td>
@@ -760,8 +760,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td>real-world</td>
-      <td><a href="https://doi.org/10.1109/TEVC.2020.3020046" target="_blank">https://doi.org/10.1109/TEVC.2020.3020046</a></td>
-      <td><a href="https://pymoo.org/problems/constrained/modact.html" target="_blank">https://pymoo.org/problems/constrained/modact.html</a></td>
+      <td><a href="https://doi.org/10.1109/TEVC.2020.3020046">https://doi.org/10.1109/TEVC.2020.3020046</a></td>
+      <td><a href="https://pymoo.org/problems/constrained/modact.html">https://pymoo.org/problems/constrained/modact.html</a></td>
     </tr>
     <tr>
       <td>IOHClustering</td>
@@ -775,12 +775,12 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td>artificial, but based on real data</td>
-      <td><a href="https://arxiv.org/pdf/2505.09233" target="_blank">https://arxiv.org/pdf/2505.09233</a></td>
-      <td><a href="https://github.com/IOHprofiler/IOHClustering" target="_blank">https://github.com/IOHprofiler/IOHClustering</a></td>
+      <td><a href="https://arxiv.org/pdf/2505.09233">https://arxiv.org/pdf/2505.09233</a></td>
+      <td><a href="https://github.com/IOHprofiler/IOHClustering">https://github.com/IOHprofiler/IOHClustering</a></td>
     </tr>
     <tr>
       <td>GNBG-II</td>
-      <td>Generalized Numerical Benchmark Generator (version 2). Also in IOH https://github.com/IOHprofiler/IOHGNBG</td>
+      <td>Generalized Numerical Benchmark Generator (version 2). Also in IOH <a href="https://github.com/IOHprofiler/IOHGNBG">https://github.com/IOHprofiler/IOHGNBG</a></td>
       <td>suite; generator</td>
       <td>1</td>
       <td>scalable</td>
@@ -790,8 +790,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td>artificial</td>
-      <td><a href="https://dl.acm.org/doi/pdf/10.1145/3712255.3734271" target="_blank">https://dl.acm.org/doi/pdf/10.1145/3712255.3734271</a></td>
-      <td><a href="https://github.com/rohitsalgotra/GNBG-II" target="_blank">https://github.com/rohitsalgotra/GNBG-II</a></td>
+      <td><a href="https://dl.acm.org/doi/pdf/10.1145/3712255.3734271">https://dl.acm.org/doi/pdf/10.1145/3712255.3734271</a></td>
+      <td><a href="https://github.com/rohitsalgotra/GNBG-II">https://github.com/rohitsalgotra/GNBG-II</a></td>
     </tr>
     <tr>
       <td>GNBG</td>
@@ -805,8 +805,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td>artificial</td>
-      <td><a href="https://arxiv.org/abs/2312.07083" target="_blank">https://arxiv.org/abs/2312.07083</a></td>
-      <td><a href="https://github.com/Danial-Yazdani/GNBG-Generator" target="_blank">https://github.com/Danial-Yazdani/GNBG-Generator</a></td>
+      <td><a href="https://arxiv.org/abs/2312.07083">https://arxiv.org/abs/2312.07083</a></td>
+      <td><a href="https://github.com/Danial-Yazdani/GNBG-Generator">https://github.com/Danial-Yazdani/GNBG-Generator</a></td>
     </tr>
     <tr>
       <td>DynamicBinVal</td>
@@ -820,8 +820,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td>artificial</td>
-      <td><a href="https://arxiv.org/pdf/2404.15837" target="_blank">https://arxiv.org/pdf/2404.15837</a></td>
-      <td><a href="https://github.com/IOHprofiler/IOHexperimenter" target="_blank">https://github.com/IOHprofiler/IOHexperimenter</a></td>
+      <td><a href="https://arxiv.org/pdf/2404.15837">https://arxiv.org/pdf/2404.15837</a></td>
+      <td><a href="https://github.com/IOHprofiler/IOHexperimenter">https://github.com/IOHprofiler/IOHexperimenter</a></td>
     </tr>
     <tr>
       <td>PBO</td>
@@ -835,8 +835,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td>artificial</td>
-      <td><a href="https://dl.acm.org/doi/pdf/10.1145/3319619.3326810" target="_blank">https://dl.acm.org/doi/pdf/10.1145/3319619.3326810</a></td>
-      <td><a href="https://github.com/IOHprofiler/IOHexperimenter" target="_blank">https://github.com/IOHprofiler/IOHexperimenter</a></td>
+      <td><a href="https://dl.acm.org/doi/pdf/10.1145/3319619.3326810">https://dl.acm.org/doi/pdf/10.1145/3319619.3326810</a></td>
+      <td><a href="https://github.com/IOHprofiler/IOHexperimenter">https://github.com/IOHprofiler/IOHexperimenter</a></td>
     </tr>
     <tr>
       <td>W-model</td>
@@ -850,8 +850,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td>artificial</td>
-      <td><a href="https://dl.acm.org/doi/abs/10.1145/3205651.3208240?casa_token=S4U_Pi9f6MwAAAAA:U9ztNTPwmupT8K3GamWZfBL7-8fqjxPtr_kprv51vdwA-REsp0EyOFGa99BtbANb0XbqyrVg795hIw" target="_blank">https://dl.acm.org/doi/abs/10.1145/3205651.3208240?casa_token=S4U_Pi9f6MwAAAAA:U9ztNTPwmupT8K3GamWZfBL7-8fqjxPtr_kprv51vdwA-REsp0EyOFGa99BtbANb0XbqyrVg795hIw</a></td>
-      <td><a href="https://github.com/thomasWeise/BBDOB_W_Model" target="_blank">https://github.com/thomasWeise/BBDOB_W_Model</a></td>
+      <td><a href="https://dl.acm.org/doi/abs/10.1145/3205651.3208240?casa_token=S4U_Pi9f6MwAAAAA:U9ztNTPwmupT8K3GamWZfBL7-8fqjxPtr_kprv51vdwA-REsp0EyOFGa99BtbANb0XbqyrVg795hIw">https://dl.acm.org/doi/abs/10.1145/3205651.3208240?casa_token=S4U_Pi9f6MwAAAAA:U9ztNTPwmupT8K3GamWZfBL7-8fqjxPtr_kprv51vdwA-REsp0EyOFGa99BtbANb0XbqyrVg795hIw</a></td>
+      <td><a href="https://github.com/thomasWeise/BBDOB_W_Model">https://github.com/thomasWeise/BBDOB_W_Model</a></td>
     </tr>
     <tr>
       <td>Submodular Optimitzation</td>
@@ -865,12 +865,12 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td>artificial</td>
-      <td><a href="https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10254181" target="_blank">https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10254181</a></td>
-      <td><a href="https://github.com/IOHprofiler/IOHexperimenter" target="_blank">https://github.com/IOHprofiler/IOHexperimenter</a></td>
+      <td><a href="https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10254181">https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10254181</a></td>
+      <td><a href="https://github.com/IOHprofiler/IOHexperimenter">https://github.com/IOHprofiler/IOHexperimenter</a></td>
     </tr>
     <tr>
       <td>CEC2013</td>
-      <td>suite used for cec2013 competition. Also in IOH https://github.com/IOHprofiler/IOHexperimenter</td>
+      <td>suite used for cec2013 competition. Also in IOH <a href="https://github.com/IOHprofiler/IOHexperimenter">https://github.com/IOHprofiler/IOHexperimenter</a></td>
       <td>suite</td>
       <td>1</td>
       <td>scalable</td>
@@ -880,12 +880,12 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td>artificial</td>
-      <td><a href="https://peerj.com/articles/cs-2671/CEC2013.pdf" target="_blank">https://peerj.com/articles/cs-2671/CEC2013.pdf</a></td>
-      <td><a href="https://github.com/P-N-Suganthan/CEC2013" target="_blank">https://github.com/P-N-Suganthan/CEC2013</a></td>
+      <td><a href="https://peerj.com/articles/cs-2671/CEC2013.pdf">https://peerj.com/articles/cs-2671/CEC2013.pdf</a></td>
+      <td><a href="https://github.com/P-N-Suganthan/CEC2013">https://github.com/P-N-Suganthan/CEC2013</a></td>
     </tr>
     <tr>
       <td>CEC2022</td>
-      <td>suite used for cec2022 competition. Also in IOH https://github.com/IOHprofiler/IOHexperimenter</td>
+      <td>suite used for cec2022 competition. Also in IOH <a href="https://github.com/IOHprofiler/IOHexperimenter">https://github.com/IOHprofiler/IOHexperimenter</a></td>
       <td>suite</td>
       <td>1</td>
       <td>scalable</td>
@@ -895,8 +895,8 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td>artificial</td>
-      <td><a href="https://github.com/P-N-Suganthan/2022-SO-BO/blob/main/CEC2022%20TR.pdf" target="_blank">https://github.com/P-N-Suganthan/2022-SO-BO/blob/main/CEC2022%20TR.pdf</a></td>
-      <td><a href="https://github.com/P-N-Suganthan/2022-SO-BO" target="_blank">https://github.com/P-N-Suganthan/2022-SO-BO</a></td>
+      <td><a href="https://github.com/P-N-Suganthan/2022-SO-BO/blob/main/CEC2022%20TR.pdf">https://github.com/P-N-Suganthan/2022-SO-BO/blob/main/CEC2022%20TR.pdf</a></td>
+      <td><a href="https://github.com/P-N-Suganthan/2022-SO-BO">https://github.com/P-N-Suganthan/2022-SO-BO</a></td>
     </tr>
     <tr>
       <td>Onemax+Sphere / Zeromax+Sphere</td>
@@ -910,7 +910,7 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td>artificial</td>
-      <td><a href="https://doi.org/10.1145/3449726.3459521" target="_blank">https://doi.org/10.1145/3449726.3459521</a></td>
+      <td><a href="https://doi.org/10.1145/3449726.3459521">https://doi.org/10.1145/3449726.3459521</a></td>
       <td>None</td>
     </tr>
     <tr>
@@ -925,7 +925,7 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td>artificial</td>
-      <td><a href="https://doi.org/10.1145/3449726.3459521" target="_blank">https://doi.org/10.1145/3449726.3459521</a></td>
+      <td><a href="https://doi.org/10.1145/3449726.3459521">https://doi.org/10.1145/3449726.3459521</a></td>
       <td>None</td>
     </tr>
     <tr>
@@ -940,16 +940,211 @@ <h2>OPL &ndash; Optimisation problem library</h2>
       <td>no</td>
       <td>no</td>
       <td>artificial</td>
-      <td><a href="https://doi.org/10.1145/3449726.3459521" target="_blank">https://doi.org/10.1145/3449726.3459521</a></td>
+      <td><a href="https://doi.org/10.1145/3449726.3459521">https://doi.org/10.1145/3449726.3459521</a></td>
       <td>None</td>
     </tr>
+    <tr>
+      <td>PorkchopPlotInterplanetaryTrajectory</td>
+      <td></td>
+      <td>suite</td>
+      <td>1</td>
+      <td>2</td>
+      <td>continuous</td>
+      <td>no</td>
+      <td>no</td>
+      <td>no</td>
+      <td>no</td>
+      <td>real-world</td>
+      <td><a href="https://doi.org/10.1109/CEC65147.2025.11042973">https://doi.org/10.1109/CEC65147.2025.11042973</a></td>
+      <td><a href="https://github.com/ShuaiqunPan/Transfer_Random_forests_BBOB_Real_world">https://github.com/ShuaiqunPan/Transfer_Random_forests_BBOB_Real_world</a></td>
+    </tr>
+    <tr>
+      <td>KinematicsRobotArm</td>
+      <td></td>
+      <td>suite</td>
+      <td>1</td>
+      <td>21</td>
+      <td>continuous</td>
+      <td>no</td>
+      <td>no</td>
+      <td>no</td>
+      <td>no</td>
+      <td>real-world</td>
+      <td><a href="https://doi.org/10.1023/A:1013258808932">https://doi.org/10.1023/A:1013258808932</a></td>
+      <td><a href="https://github.com/ShuaiqunPan/Transfer_Random_forests_BBOB_Real_world">https://github.com/ShuaiqunPan/Transfer_Random_forests_BBOB_Real_world</a></td>
+    </tr>
+    <tr>
+      <td>VehicleDynamics</td>
+      <td></td>
+      <td>suite</td>
+      <td>1</td>
+      <td>2</td>
+      <td>continuous</td>
+      <td>no</td>
+      <td>no</td>
+      <td>no</td>
+      <td>no</td>
+      <td>real-world</td>
+      <td><a href="https://www.scitepress.org/Papers/2023/121580/121580.pdf">https://www.scitepress.org/Papers/2023/121580/121580.pdf</a></td>
+      <td><a href="https://zenodo.org/records/8307853">https://zenodo.org/records/8307853</a></td>
+    </tr>
+    <tr>
+      <td>MECHBench</td>
+      <td>This is a set of problems with inspiration from Structural Mechanics Design Optimization. The suite comprises three physical models, from which the user may define different kind of problems which impact the final design output.</td>
+      <td>Problem Suite</td>
+      <td>1</td>
+      <td>scalable'</td>
+      <td>Continuous</td>
+      <td>yes</td>
+      <td>no</td>
+      <td>no</td>
+      <td>no</td>
+      <td>Real-World Application</td>
+      <td><a href="https://arxiv.org/abs/2511.10821">https://arxiv.org/abs/2511.10821</a></td>
+      <td><a href="https://github.com/BayesOptApp/MECHBench">https://github.com/BayesOptApp/MECHBench</a></td>
+    </tr>
+    <tr>
+      <td>EXPObench</td>
+      <td>Wind farm layout optimization, gas filter design, pipe shape optimization, hyperparameter tuning, and hospital simulation</td>
+      <td>Problem Suite</td>
+      <td>1</td>
+      <td>10 to 135</td>
+      <td>Continuous, Integer, Categorical, Conditional</td>
+      <td>yes</td>
+      <td>no</td>
+      <td>yes</td>
+      <td>no</td>
+      <td>Real-World Application</td>
+      <td><a href="https://doi.org/10.1016/j.asoc.2023.110744">https://doi.org/10.1016/j.asoc.2023.110744</a></td>
+      <td><a href="https://github.com/AlgTUDelft/ExpensiveOptimBenchmark">https://github.com/AlgTUDelft/ExpensiveOptimBenchmark</a></td>
+    </tr>
+    <tr>
+      <td>Gasoline direct injection engine design</td>
+      <td>A multi-objective optimization problem seeking to minimize fuel consumption and NOx emissions over a two-minute dynamic duty cycle, subject to five constraints (turbine inlet temperature, number of knock occurrences, peak cylinder pressure, peak cylinder pressure rise, total work). Seven decision variables are defined: four define the hardware choices of cylinder compression ratio, turbo machinery and EGR cooler sizing; three relate to control variables that parameterise the engine control logic.</td>
+      <td>Single Problem</td>
+      <td>2</td>
+      <td>7</td>
+      <td>Continuous, Ordinal</td>
+      <td>yes</td>
+      <td>no</td>
+      <td>no</td>
+      <td>yes</td>
+      <td>Real-World Application</td>
+      <td></td>
+      <td><a href="https://doi.org/10.1016/j.ejor.2022.08.032">https://doi.org/10.1016/j.ejor.2022.08.032</a></td>
+    </tr>
+    <tr>
+      <td>BEACON</td>
+      <td>Generator for bi-objective benchmark problems with explicitly controlled correlations in continuous spaces.</td>
+      <td>Generator</td>
+      <td>2</td>
+      <td>scalable</td>
+      <td>Continuous</td>
+      <td>no</td>
+      <td>no</td>
+      <td>no</td>
+      <td>no</td>
+      <td>Artificially Generated</td>
+      <td><a href="https://dl.acm.org/doi/10.1145/3712255.3734303">https://dl.acm.org/doi/10.1145/3712255.3734303</a></td>
+      <td><a href="https://github.com/Stebbet/BEACON/">https://github.com/Stebbet/BEACON/</a></td>
+    </tr>
+    <tr>
+      <td>TulipaEnergy</td>
+      <td>Determine the optimal investment and operation decisions  for different types of assets in the energy system (production, consumption, conversion, storage, and transport), while minimizing loss of load.</td>
+      <td>Problem Suite</td>
+      <td>1</td>
+      <td>scalable</td>
+      <td>Continuous</td>
+      <td>yes</td>
+      <td>no</td>
+      <td>yes</td>
+      <td>yes</td>
+      <td>Real-World Application</td>
+      <td><a href="https://tulipaenergy.github.io/TulipaEnergyModel.jl/stable/40-scientific-foundation/45-scientific-references">https://tulipaenergy.github.io/TulipaEnergyModel.jl/stable/40-scientific-foundation/45-scientific-references</a></td>
+      <td><a href="https://tulipaenergy.github.io/TulipaEnergyModel.jl/stable/">https://tulipaenergy.github.io/TulipaEnergyModel.jl/stable/</a></td>
+    </tr>
+    <tr>
+      <td>ATO</td>
+      <td>Parameters of the Modules of the Automatic Train Operation should be optimized. The parameters are continuous with different ranges. There are two objectives (minimizing energy consumption, minimizing driving duration.</td>
+      <td>Single Problem</td>
+      <td>2</td>
+      <td>10</td>
+      <td>Continuous</td>
+      <td>no</td>
+      <td>no</td>
+      <td>no</td>
+      <td>no</td>
+      <td>Real-World Application</td>
+      <td></td>
+      <td>-</td>
+    </tr>
+    <tr>
+      <td>Brachytherapy treatment planning</td>
+      <td>Treatment planning for internal radiation therapy</td>
+      <td>Problem Suite</td>
+      <td>2-3</td>
+      <td>100-500</td>
+      <td>Continuous</td>
+      <td>yes</td>
+      <td>no</td>
+      <td>no</td>
+      <td>yes</td>
+      <td>Real-World Application</td>
+      <td><a href="https://www.sciencedirect.com/science/article/pii/S1538472123016781">https://www.sciencedirect.com/science/article/pii/S1538472123016781</a></td>
+      <td></td>
+    </tr>
+    <tr>
+      <td>FleetOpt</td>
+      <td>Healthcare organisation in the UK provided data about their current fleet of vehicles to conduct non-emergency heathcare trips in the Argyll and Bute region of Scotland, UK. They also provided historical data about the trips the vehicles took and about the bases which the vehicles return to. The aim is to reduce the existing fleet of vehicles while still ensuring all trips can be covered. Moving a vehicle from one base to another to help cover trips is OK as long as the original base can still cover its trips. Link to paper with more details: <a href="https://dl.acm.org/doi/abs/10.1145/3638530.3664137">https://dl.acm.org/doi/abs/10.1145/3638530.3664137</a></td>
+      <td>Single Problem</td>
+      <td>1</td>
+      <td>Upper level: 54; lower level: 13208</td>
+      <td>Integer</td>
+      <td>yes</td>
+      <td>no</td>
+      <td>no</td>
+      <td>no</td>
+      <td>Real-World Application</td>
+      <td><a href="https://dl.acm.org/doi/abs/10.1145/3638530.3664137">https://dl.acm.org/doi/abs/10.1145/3638530.3664137</a></td>
+      <td>Not public: was done for real client with their private data</td>
+    </tr>
+    <tr>
+      <td>Building spatial design</td>
+      <td>Optimise the spatial layout of a building to: minimise energy consumption for climate control, and minimise the strain on the structure</td>
+      <td>Single Problem</td>
+      <td>2</td>
+      <td>scalable depending on problem size (e.g. 90 for)</td>
+      <td>Continuous, Boolean</td>
+      <td>yes</td>
+      <td>no</td>
+      <td>no</td>
+      <td>no</td>
+      <td>Real-World Application</td>
+      <td><a href="https://hdl.handle.net/1887/81789">https://hdl.handle.net/1887/81789</a></td>
+      <td><a href="https://github.com/TUe-excellent-buildings/BSO-toolbox">https://github.com/TUe-excellent-buildings/BSO-toolbox</a></td>
+    </tr>
+    <tr>
+      <td>Electric Motor Design Optimization</td>
+      <td>The goal is to find a design of a synchronous electric motor for power steering systems that minimizes costs and satisfies all constraints.</td>
+      <td>Single Problem</td>
+      <td>1</td>
+      <td>13</td>
+      <td>Continuous, Integer</td>
+      <td>yes</td>
+      <td>no</td>
+      <td>yes</td>
+      <td>no</td>
+      <td>Real-World Application</td>
+      <td><a href="https://dis.ijs.si/tea/Publications/Tusar23Multistep.pdf">https://dis.ijs.si/tea/Publications/Tusar23Multistep.pdf</a> (paper in Slovene)</td>
+      <td>Implementation not freely available</td>
+    </tr>
   </tbody>
 <tfoot><tr><th>name</th> <th>textual description</th> <th>suite/generator/single</th> <th>objectives</th> <th>dimensionality</th> <th>variable type</th> <th>constraints</th> <th>dynamic</th> <th>noise</th> <th>multi-fidelity</th> <th>source (real-world/artificial)</th> <th>reference</th> <th>implementation</th></tr> </tfoot></table>
 
 <script>
 new DataTable('#problems', {
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+        topStart: 'search',
         topEnd: null,
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diff --git a/docs/javascript.html b/docs/javascript.html
index 5b51331..a194ca7 100644
--- a/docs/javascript.html
+++ b/docs/javascript.html
@@ -3,7 +3,7 @@
 <script>
 new DataTable('#problems', {
     layout: {
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+        topStart: 'search',
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diff --git a/docs/problems.html b/docs/problems.html
index 92f077d..ff51d79 100644
--- a/docs/problems.html
+++ b/docs/problems.html
@@ -29,8 +29,8 @@
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1080/10556788.2020.1808977" target="_blank">https://doi.org/10.1080/10556788.2020.1808977</a></td>
-      <td><a href="https://github.com/numbbo/coco" target="_blank">https://github.com/numbbo/coco</a></td>
+      <td><a href="https://doi.org/10.1080/10556788.2020.1808977">https://doi.org/10.1080/10556788.2020.1808977</a></td>
+      <td><a href="https://github.com/numbbo/coco">https://github.com/numbbo/coco</a></td>
     </tr>
     <tr>
       <td>BBOB-biobj</td>
@@ -44,8 +44,8 @@
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.48550/arXiv.1604.00359" target="_blank">https://doi.org/10.48550/arXiv.1604.00359</a></td>
-      <td><a href="https://github.com/numbbo/coco" target="_blank">https://github.com/numbbo/coco</a></td>
+      <td><a href="https://doi.org/10.48550/arXiv.1604.00359">https://doi.org/10.48550/arXiv.1604.00359</a></td>
+      <td><a href="https://github.com/numbbo/coco">https://github.com/numbbo/coco</a></td>
     </tr>
     <tr>
       <td>BBOB-noisy</td>
@@ -59,8 +59,8 @@
       <td>yes</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://hal.inria.fr/inria-00369466" target="_blank">https://hal.inria.fr/inria-00369466</a></td>
-      <td><a href="https://web.archive.org/web/20210416065610/https://coco.gforge.inria.fr/doku.php?id=downloads" target="_blank">https://web.archive.org/web/20210416065610/https://coco.gforge.inria.fr/doku.php?id=downloads</a></td>
+      <td><a href="https://hal.inria.fr/inria-00369466">https://hal.inria.fr/inria-00369466</a></td>
+      <td><a href="https://web.archive.org/web/20210416065610/https://coco.gforge.inria.fr/doku.php?id=downloads">https://web.archive.org/web/20210416065610/https://coco.gforge.inria.fr/doku.php?id=downloads</a></td>
     </tr>
     <tr>
       <td>BBOB-largescale</td>
@@ -74,8 +74,8 @@
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.48550/arXiv.1903.06396" target="_blank">https://doi.org/10.48550/arXiv.1903.06396</a></td>
-      <td><a href="https://github.com/numbbo/coco" target="_blank">https://github.com/numbbo/coco</a></td>
+      <td><a href="https://doi.org/10.48550/arXiv.1903.06396">https://doi.org/10.48550/arXiv.1903.06396</a></td>
+      <td><a href="https://github.com/numbbo/coco">https://github.com/numbbo/coco</a></td>
     </tr>
     <tr>
       <td>BBOB-mixint</td>
@@ -89,8 +89,8 @@
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1145/3321707.3321868" target="_blank">https://doi.org/10.1145/3321707.3321868</a></td>
-      <td><a href="https://github.com/numbbo/coco" target="_blank">https://github.com/numbbo/coco</a></td>
+      <td><a href="https://doi.org/10.1145/3321707.3321868">https://doi.org/10.1145/3321707.3321868</a></td>
+      <td><a href="https://github.com/numbbo/coco">https://github.com/numbbo/coco</a></td>
     </tr>
     <tr>
       <td>BBOB-biobj-mixint</td>
@@ -104,8 +104,8 @@
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1145/3321707.3321868" target="_blank">https://doi.org/10.1145/3321707.3321868</a></td>
-      <td><a href="https://github.com/numbbo/coco" target="_blank">https://github.com/numbbo/coco</a></td>
+      <td><a href="https://doi.org/10.1145/3321707.3321868">https://doi.org/10.1145/3321707.3321868</a></td>
+      <td><a href="https://github.com/numbbo/coco">https://github.com/numbbo/coco</a></td>
     </tr>
     <tr>
       <td>BBOB-constrained</td>
@@ -119,8 +119,8 @@
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="http://numbbo.github.io/coco-doc/bbob-constrained/" target="_blank">http://numbbo.github.io/coco-doc/bbob-constrained/</a></td>
-      <td><a href="https://github.com/numbbo/coco" target="_blank">https://github.com/numbbo/coco</a></td>
+      <td><a href="http://numbbo.github.io/coco-doc/bbob-constrained/">http://numbbo.github.io/coco-doc/bbob-constrained/</a></td>
+      <td><a href="https://github.com/numbbo/coco">https://github.com/numbbo/coco</a></td>
     </tr>
     <tr>
       <td>MOrepo</td>
@@ -135,7 +135,7 @@
       <td>no</td>
       <td></td>
       <td></td>
-      <td><a href="https://github.com/MCDMSociety/MOrepo" target="_blank">https://github.com/MCDMSociety/MOrepo</a></td>
+      <td><a href="https://github.com/MCDMSociety/MOrepo">https://github.com/MCDMSociety/MOrepo</a></td>
     </tr>
     <tr>
       <td>ZDT</td>
@@ -149,8 +149,8 @@
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1162/106365600568202" target="_blank">https://doi.org/10.1162/106365600568202</a></td>
-      <td><a href="https://github.com/anyoptimization/pymoo" target="_blank">https://github.com/anyoptimization/pymoo</a></td>
+      <td><a href="https://doi.org/10.1162/106365600568202">https://doi.org/10.1162/106365600568202</a></td>
+      <td><a href="https://github.com/anyoptimization/pymoo">https://github.com/anyoptimization/pymoo</a></td>
     </tr>
     <tr>
       <td>DTLZ</td>
@@ -164,8 +164,8 @@
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1109/CEC.2002.1007032" target="_blank">https://doi.org/10.1109/CEC.2002.1007032</a></td>
-      <td><a href="https://pymoo.org/problems/many/dtlz.html" target="_blank">https://pymoo.org/problems/many/dtlz.html</a></td>
+      <td><a href="https://doi.org/10.1109/CEC.2002.1007032">https://doi.org/10.1109/CEC.2002.1007032</a></td>
+      <td><a href="https://pymoo.org/problems/many/dtlz.html">https://pymoo.org/problems/many/dtlz.html</a></td>
     </tr>
     <tr>
       <td>WFG</td>
@@ -179,8 +179,8 @@
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1109/TEVC.2005.861417" target="_blank">https://doi.org/10.1109/TEVC.2005.861417</a></td>
-      <td><a href="https://pymoo.org/problems/many/wfg.html" target="_blank">https://pymoo.org/problems/many/wfg.html</a></td>
+      <td><a href="https://doi.org/10.1109/TEVC.2005.861417">https://doi.org/10.1109/TEVC.2005.861417</a></td>
+      <td><a href="https://pymoo.org/problems/many/wfg.html">https://pymoo.org/problems/many/wfg.html</a></td>
     </tr>
     <tr>
       <td>CDMP</td>
@@ -194,7 +194,7 @@
       <td>?</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1145/3321707.3321878" target="_blank">https://doi.org/10.1145/3321707.3321878</a></td>
+      <td><a href="https://doi.org/10.1145/3321707.3321878">https://doi.org/10.1145/3321707.3321878</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -209,7 +209,7 @@
       <td>?</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1109/TCYB.2019.2896021" target="_blank">https://doi.org/10.1109/TCYB.2019.2896021</a></td>
+      <td><a href="https://doi.org/10.1109/TCYB.2019.2896021">https://doi.org/10.1109/TCYB.2019.2896021</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -224,7 +224,7 @@
       <td>?</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1016/j.swevo.2019.02.003" target="_blank">https://doi.org/10.1016/j.swevo.2019.02.003</a></td>
+      <td><a href="https://doi.org/10.1016/j.swevo.2019.02.003">https://doi.org/10.1016/j.swevo.2019.02.003</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -239,7 +239,7 @@
       <td>?</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1109/CEC.2019.8790277" target="_blank">https://doi.org/10.1109/CEC.2019.8790277</a></td>
+      <td><a href="https://doi.org/10.1109/CEC.2019.8790277">https://doi.org/10.1109/CEC.2019.8790277</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -254,7 +254,7 @@
       <td>optional</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1016/j.asoc.2020.106139" target="_blank">https://doi.org/10.1016/j.asoc.2020.106139</a></td>
+      <td><a href="https://doi.org/10.1016/j.asoc.2020.106139">https://doi.org/10.1016/j.asoc.2020.106139</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -269,8 +269,8 @@
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.48550/arXiv.2110.08033" target="_blank">https://doi.org/10.48550/arXiv.2110.08033</a></td>
-      <td><a href="https://github.com/songbai-liu/etmo" target="_blank">https://github.com/songbai-liu/etmo</a></td>
+      <td><a href="https://doi.org/10.48550/arXiv.2110.08033">https://doi.org/10.48550/arXiv.2110.08033</a></td>
+      <td><a href="https://github.com/songbai-liu/etmo">https://github.com/songbai-liu/etmo</a></td>
     </tr>
     <tr>
       <td>MMOPP</td>
@@ -284,8 +284,8 @@
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="http://www5.zzu.edu.cn/system/_content/download.jsp?urltype=news.DownloadAttachUrl&owner=1327567121&wbfileid=4764412" target="_blank">http://www5.zzu.edu.cn/system/_content/download.jsp?urltype=news.DownloadAttachUrl&amp;owner=1327567121&amp;wbfileid=4764412</a></td>
-      <td><a href="http://www5.zzu.edu.cn/ecilab/info/1036/1251.htm" target="_blank">http://www5.zzu.edu.cn/ecilab/info/1036/1251.htm</a></td>
+      <td><a href="http://www5.zzu.edu.cn/system/_content/download.jsp?urltype=news.DownloadAttachUrl&owner=1327567121&wbfileid=4764412">http://www5.zzu.edu.cn/system/_content/download.jsp?urltype=news.DownloadAttachUrl&owner=1327567121&wbfileid=4764412</a></td>
+      <td><a href="http://www5.zzu.edu.cn/ecilab/info/1036/1251.htm">http://www5.zzu.edu.cn/ecilab/info/1036/1251.htm</a></td>
     </tr>
     <tr>
       <td>CFD</td>
@@ -299,8 +299,8 @@
       <td>no</td>
       <td>no</td>
       <td>real world</td>
-      <td><a href="https://doi.org/10.1007/978-3-319-99259-4_24" target="_blank">https://doi.org/10.1007/978-3-319-99259-4_24</a></td>
-      <td><a href="https://bitbucket.org/arahat/cfd-test-problem-suite" target="_blank">https://bitbucket.org/arahat/cfd-test-problem-suite</a></td>
+      <td><a href="https://doi.org/10.1007/978-3-319-99259-4_24">https://doi.org/10.1007/978-3-319-99259-4_24</a></td>
+      <td><a href="https://bitbucket.org/arahat/cfd-test-problem-suite">https://bitbucket.org/arahat/cfd-test-problem-suite</a></td>
     </tr>
     <tr>
       <td>GBEA</td>
@@ -314,7 +314,7 @@
       <td>yes</td>
       <td>no</td>
       <td>real world</td>
-      <td><a href="https://doi.org/10.1145/3321707.3321805" target="_blank">https://doi.org/10.1145/3321707.3321805</a></td>
+      <td><a href="https://doi.org/10.1145/3321707.3321805">https://doi.org/10.1145/3321707.3321805</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -329,8 +329,8 @@
       <td>no</td>
       <td>no</td>
       <td>real world</td>
-      <td><a href="https://doi.org/10.1145/3205651.3205702" target="_blank">https://doi.org/10.1145/3205651.3205702</a></td>
-      <td><a href="http://ladse.eng.isas.jaxa.jp/benchmark/" target="_blank">http://ladse.eng.isas.jaxa.jp/benchmark/</a></td>
+      <td><a href="https://doi.org/10.1145/3205651.3205702">https://doi.org/10.1145/3205651.3205702</a></td>
+      <td><a href="http://ladse.eng.isas.jaxa.jp/benchmark/">http://ladse.eng.isas.jaxa.jp/benchmark/</a></td>
     </tr>
     <tr>
       <td>EMO2017</td>
@@ -344,8 +344,8 @@
       <td>no</td>
       <td>no</td>
       <td>real world</td>
-      <td><a href="https://www.ini.rub.de/PEOPLE/glasmtbl/projects/bbcomp/" target="_blank">https://www.ini.rub.de/PEOPLE/glasmtbl/projects/bbcomp/</a></td>
-      <td><a href="https://www.ini.rub.de/PEOPLE/glasmtbl/projects/bbcomp/downloads/realworld-problems-bbcomp-EMO-2017.zip" target="_blank">https://www.ini.rub.de/PEOPLE/glasmtbl/projects/bbcomp/downloads/realworld-problems-bbcomp-EMO-2017.zip</a></td>
+      <td><a href="https://www.ini.rub.de/PEOPLE/glasmtbl/projects/bbcomp/">https://www.ini.rub.de/PEOPLE/glasmtbl/projects/bbcomp/</a></td>
+      <td><a href="https://www.ini.rub.de/PEOPLE/glasmtbl/projects/bbcomp/downloads/realworld-problems-bbcomp-EMO-2017.zip">https://www.ini.rub.de/PEOPLE/glasmtbl/projects/bbcomp/downloads/realworld-problems-bbcomp-EMO-2017.zip</a></td>
     </tr>
     <tr>
       <td>JSEC2019</td>
@@ -359,8 +359,8 @@
       <td>no</td>
       <td>no</td>
       <td>real world</td>
-      <td><a href="http://www.jpnsec.org/files/competition2019/EC-Symposium-2019-Competition-English.html" target="_blank">http://www.jpnsec.org/files/competition2019/EC-Symposium-2019-Competition-English.html</a></td>
-      <td><a href="http://www.jpnsec.org/files/competition2019/EC-Symposium-2019-Competition-English.html" target="_blank">http://www.jpnsec.org/files/competition2019/EC-Symposium-2019-Competition-English.html</a></td>
+      <td><a href="http://www.jpnsec.org/files/competition2019/EC-Symposium-2019-Competition-English.html">http://www.jpnsec.org/files/competition2019/EC-Symposium-2019-Competition-English.html</a></td>
+      <td><a href="http://www.jpnsec.org/files/competition2019/EC-Symposium-2019-Competition-English.html">http://www.jpnsec.org/files/competition2019/EC-Symposium-2019-Competition-English.html</a></td>
     </tr>
     <tr>
       <td>RE</td>
@@ -374,8 +374,8 @@
       <td>no</td>
       <td>no</td>
       <td>real world like</td>
-      <td><a href="https://doi.org/10.1016/j.asoc.2020.106078" target="_blank">https://doi.org/10.1016/j.asoc.2020.106078</a></td>
-      <td><a href="https://github.com/ryojitanabe/reproblems" target="_blank">https://github.com/ryojitanabe/reproblems</a></td>
+      <td><a href="https://doi.org/10.1016/j.asoc.2020.106078">https://doi.org/10.1016/j.asoc.2020.106078</a></td>
+      <td><a href="https://github.com/ryojitanabe/reproblems">https://github.com/ryojitanabe/reproblems</a></td>
     </tr>
     <tr>
       <td>CRE</td>
@@ -389,8 +389,8 @@
       <td>no</td>
       <td>no</td>
       <td>real world like</td>
-      <td><a href="https://doi.org/10.1016/j.asoc.2020.106078" target="_blank">https://doi.org/10.1016/j.asoc.2020.106078</a></td>
-      <td><a href="https://github.com/ryojitanabe/reproblems" target="_blank">https://github.com/ryojitanabe/reproblems</a></td>
+      <td><a href="https://doi.org/10.1016/j.asoc.2020.106078">https://doi.org/10.1016/j.asoc.2020.106078</a></td>
+      <td><a href="https://github.com/ryojitanabe/reproblems">https://github.com/ryojitanabe/reproblems</a></td>
     </tr>
     <tr>
       <td>Radar waveform</td>
@@ -404,8 +404,8 @@
       <td>no</td>
       <td>no</td>
       <td>real world</td>
-      <td><a href="https://doi.org/10.1007/978-3-540-70928-2_53" target="_blank">https://doi.org/10.1007/978-3-540-70928-2_53</a></td>
-      <td><a href="http://code.evanhughes.org/" target="_blank">http://code.evanhughes.org/</a></td>
+      <td><a href="https://doi.org/10.1007/978-3-540-70928-2_53">https://doi.org/10.1007/978-3-540-70928-2_53</a></td>
+      <td><a href="http://code.evanhughes.org/">http://code.evanhughes.org/</a></td>
     </tr>
     <tr>
       <td>MF2</td>
@@ -419,8 +419,8 @@
       <td>no</td>
       <td>yes</td>
       <td></td>
-      <td><a href="https://doi.org/10.21105/joss.02049" target="_blank">https://doi.org/10.21105/joss.02049</a></td>
-      <td><a href="https://github.com/sjvrijn/mf2" target="_blank">https://github.com/sjvrijn/mf2</a></td>
+      <td><a href="https://doi.org/10.21105/joss.02049">https://doi.org/10.21105/joss.02049</a></td>
+      <td><a href="https://github.com/sjvrijn/mf2">https://github.com/sjvrijn/mf2</a></td>
     </tr>
     <tr>
       <td>AMVOP</td>
@@ -434,7 +434,7 @@
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1109/TEVC.2013.2281531" target="_blank">https://doi.org/10.1109/TEVC.2013.2281531</a></td>
+      <td><a href="https://doi.org/10.1109/TEVC.2013.2281531">https://doi.org/10.1109/TEVC.2013.2281531</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -449,7 +449,7 @@
       <td>no</td>
       <td>no</td>
       <td>real world</td>
-      <td><a href="https://doi.org/10.1109/TEVC.2013.2281531" target="_blank">https://doi.org/10.1109/TEVC.2013.2281531</a></td>
+      <td><a href="https://doi.org/10.1109/TEVC.2013.2281531">https://doi.org/10.1109/TEVC.2013.2281531</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -464,8 +464,8 @@
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.48550/arXiv.2305.12221" target="_blank">https://doi.org/10.48550/arXiv.2305.12221</a></td>
-      <td><a href="https://github.com/IOHprofiler/IOHexperimenter/" target="_blank">https://github.com/IOHprofiler/IOHexperimenter/</a></td>
+      <td><a href="https://doi.org/10.48550/arXiv.2305.12221">https://doi.org/10.48550/arXiv.2305.12221</a></td>
+      <td><a href="https://github.com/IOHprofiler/IOHexperimenter/">https://github.com/IOHprofiler/IOHexperimenter/</a></td>
     </tr>
     <tr>
       <td>ρMNK-Landscapes</td>
@@ -479,8 +479,8 @@
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1016/j.ejor.2012.12.019" target="_blank">https://doi.org/10.1016/j.ejor.2012.12.019</a></td>
-      <td><a href="https://gitlab.com/aliefooghe/mocobench/" target="_blank">https://gitlab.com/aliefooghe/mocobench/</a></td>
+      <td><a href="https://doi.org/10.1016/j.ejor.2012.12.019">https://doi.org/10.1016/j.ejor.2012.12.019</a></td>
+      <td><a href="https://gitlab.com/aliefooghe/mocobench/">https://gitlab.com/aliefooghe/mocobench/</a></td>
     </tr>
     <tr>
       <td>mUBQP</td>
@@ -494,8 +494,8 @@
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1016/j.asoc.2013.11.008" target="_blank">https://doi.org/10.1016/j.asoc.2013.11.008</a></td>
-      <td><a href="https://gitlab.com/aliefooghe/mocobench/" target="_blank">https://gitlab.com/aliefooghe/mocobench/</a></td>
+      <td><a href="https://doi.org/10.1016/j.asoc.2013.11.008">https://doi.org/10.1016/j.asoc.2013.11.008</a></td>
+      <td><a href="https://gitlab.com/aliefooghe/mocobench/">https://gitlab.com/aliefooghe/mocobench/</a></td>
     </tr>
     <tr>
       <td>ρmTSP</td>
@@ -509,8 +509,8 @@
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1007/978-3-319-45823-6_40" target="_blank">https://doi.org/10.1007/978-3-319-45823-6_40</a></td>
-      <td><a href="https://gitlab.com/aliefooghe/mocobench/" target="_blank">https://gitlab.com/aliefooghe/mocobench/</a></td>
+      <td><a href="https://doi.org/10.1007/978-3-319-45823-6_40">https://doi.org/10.1007/978-3-319-45823-6_40</a></td>
+      <td><a href="https://gitlab.com/aliefooghe/mocobench/">https://gitlab.com/aliefooghe/mocobench/</a></td>
     </tr>
     <tr>
       <td>CEC2015-DMOO</td>
@@ -539,8 +539,8 @@
       <td>no</td>
       <td>optional</td>
       <td>Real-world-like</td>
-      <td><a href="https://doi.org/10.1145/3638530.3654299" target="_blank">https://doi.org/10.1145/3638530.3654299</a></td>
-      <td><a href="https://github.com/qrenau/Ealain" target="_blank">https://github.com/qrenau/Ealain</a></td>
+      <td><a href="https://doi.org/10.1145/3638530.3654299">https://doi.org/10.1145/3638530.3654299</a></td>
+      <td><a href="https://github.com/qrenau/Ealain">https://github.com/qrenau/Ealain</a></td>
     </tr>
     <tr>
       <td>MA-BBOB</td>
@@ -554,8 +554,8 @@
       <td>no</td>
       <td>no</td>
       <td>artificial</td>
-      <td><a href="https://doi.org/10.1145/3673908" target="_blank">https://doi.org/10.1145/3673908</a></td>
-      <td><a href="https://github.com/IOHprofiler/IOHexperimenter/blob/master/example/Competitions/MA-BBOB/Example_MABBOB.ipynb" target="_blank">https://github.com/IOHprofiler/IOHexperimenter/blob/master/example/Competitions/MA-BBOB/Example_MABBOB.ipynb</a></td>
+      <td><a href="https://doi.org/10.1145/3673908">https://doi.org/10.1145/3673908</a></td>
+      <td><a href="https://github.com/IOHprofiler/IOHexperimenter/blob/master/example/Competitions/MA-BBOB/Example_MABBOB.ipynb">https://github.com/IOHprofiler/IOHexperimenter/blob/master/example/Competitions/MA-BBOB/Example_MABBOB.ipynb</a></td>
     </tr>
     <tr>
       <td>MPM2</td>
@@ -569,8 +569,8 @@
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://ls11-www.cs.tu-dortmund.de/_media/techreports/tr15-01.pdf" target="_blank">https://ls11-www.cs.tu-dortmund.de/_media/techreports/tr15-01.pdf</a></td>
-      <td><a href="https://github.com/jakobbossek/smoof/blob/master/inst/mpm2.py" target="_blank">https://github.com/jakobbossek/smoof/blob/master/inst/mpm2.py</a></td>
+      <td><a href="https://ls11-www.cs.tu-dortmund.de/_media/techreports/tr15-01.pdf">https://ls11-www.cs.tu-dortmund.de/_media/techreports/tr15-01.pdf</a></td>
+      <td><a href="https://github.com/jakobbossek/smoof/blob/master/inst/mpm2.py">https://github.com/jakobbossek/smoof/blob/master/inst/mpm2.py</a></td>
     </tr>
     <tr>
       <td>Convex DTLZ2</td>
@@ -584,7 +584,7 @@
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1109/TEVC.2013.2281535" target="_blank">https://doi.org/10.1109/TEVC.2013.2281535</a></td>
+      <td><a href="https://doi.org/10.1109/TEVC.2013.2281535">https://doi.org/10.1109/TEVC.2013.2281535</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -599,7 +599,7 @@
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1109/TEVC.2013.2281534" target="_blank">https://doi.org/10.1109/TEVC.2013.2281534</a></td>
+      <td><a href="https://doi.org/10.1109/TEVC.2013.2281534">https://doi.org/10.1109/TEVC.2013.2281534</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -614,7 +614,7 @@
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1109/TEVC.2016.2587749" target="_blank">https://doi.org/10.1109/TEVC.2016.2587749</a></td>
+      <td><a href="https://doi.org/10.1109/TEVC.2016.2587749">https://doi.org/10.1109/TEVC.2016.2587749</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -629,7 +629,7 @@
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1109/TEVC.2016.2587749" target="_blank">https://doi.org/10.1109/TEVC.2016.2587749</a></td>
+      <td><a href="https://doi.org/10.1109/TEVC.2016.2587749">https://doi.org/10.1109/TEVC.2016.2587749</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -644,7 +644,7 @@
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1145/1143997.1144179" target="_blank">https://doi.org/10.1145/1143997.1144179</a></td>
+      <td><a href="https://doi.org/10.1145/1143997.1144179">https://doi.org/10.1145/1143997.1144179</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -659,7 +659,7 @@
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1145/1143997.1144179" target="_blank">https://doi.org/10.1145/1143997.1144179</a></td>
+      <td><a href="https://doi.org/10.1145/1143997.1144179">https://doi.org/10.1145/1143997.1144179</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -674,7 +674,7 @@
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1145/1143997.1144179" target="_blank">https://doi.org/10.1145/1143997.1144179</a></td>
+      <td><a href="https://doi.org/10.1145/1143997.1144179">https://doi.org/10.1145/1143997.1144179</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -689,7 +689,7 @@
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1145/1143997.1144179" target="_blank">https://doi.org/10.1145/1143997.1144179</a></td>
+      <td><a href="https://doi.org/10.1145/1143997.1144179">https://doi.org/10.1145/1143997.1144179</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -704,7 +704,7 @@
       <td>no</td>
       <td>no</td>
       <td></td>
-      <td><a href="https://doi.org/10.1145/1143997.1144179" target="_blank">https://doi.org/10.1145/1143997.1144179</a></td>
+      <td><a href="https://doi.org/10.1145/1143997.1144179">https://doi.org/10.1145/1143997.1144179</a></td>
       <td>?</td>
     </tr>
     <tr>
@@ -719,12 +719,12 @@
       <td>no</td>
       <td>no</td>
       <td>artificial</td>
-      <td><a href="https://www.academia.edu/download/94499025/TR-CEC2018-DMOP-Competition.pdf" target="_blank">https://www.academia.edu/download/94499025/TR-CEC2018-DMOP-Competition.pdf</a></td>
-      <td><a href="https://pymoo.org/problems/dynamic/df.html" target="_blank">https://pymoo.org/problems/dynamic/df.html</a></td>
+      <td><a href="https://www.academia.edu/download/94499025/TR-CEC2018-DMOP-Competition.pdf">https://www.academia.edu/download/94499025/TR-CEC2018-DMOP-Competition.pdf</a></td>
+      <td><a href="https://pymoo.org/problems/dynamic/df.html">https://pymoo.org/problems/dynamic/df.html</a></td>
     </tr>
     <tr>
       <td>MODAct - multiobjective design of actuators</td>
-      <td>Realistic Constrained Multi-Objective Optimization Benchmark Problems from Design. Need the https://github.com/epfl-lamd/modact package installed; evaluation times around 20ms</td>
+      <td>Realistic Constrained Multi-Objective Optimization Benchmark Problems from Design. Need the <a href="https://github.com/epfl-lamd/modact">https://github.com/epfl-lamd/modact</a> package installed; evaluation times around 20ms</td>
       <td>suite</td>
       <td>2 3 4 or 5</td>
       <td>20</td>
@@ -734,8 +734,8 @@
       <td>no</td>
       <td>no</td>
       <td>real-world</td>
-      <td><a href="https://doi.org/10.1109/TEVC.2020.3020046" target="_blank">https://doi.org/10.1109/TEVC.2020.3020046</a></td>
-      <td><a href="https://pymoo.org/problems/constrained/modact.html" target="_blank">https://pymoo.org/problems/constrained/modact.html</a></td>
+      <td><a href="https://doi.org/10.1109/TEVC.2020.3020046">https://doi.org/10.1109/TEVC.2020.3020046</a></td>
+      <td><a href="https://pymoo.org/problems/constrained/modact.html">https://pymoo.org/problems/constrained/modact.html</a></td>
     </tr>
     <tr>
       <td>IOHClustering</td>
@@ -749,12 +749,12 @@
       <td>no</td>
       <td>no</td>
       <td>artificial, but based on real data</td>
-      <td><a href="https://arxiv.org/pdf/2505.09233" target="_blank">https://arxiv.org/pdf/2505.09233</a></td>
-      <td><a href="https://github.com/IOHprofiler/IOHClustering" target="_blank">https://github.com/IOHprofiler/IOHClustering</a></td>
+      <td><a href="https://arxiv.org/pdf/2505.09233">https://arxiv.org/pdf/2505.09233</a></td>
+      <td><a href="https://github.com/IOHprofiler/IOHClustering">https://github.com/IOHprofiler/IOHClustering</a></td>
     </tr>
     <tr>
       <td>GNBG-II</td>
-      <td>Generalized Numerical Benchmark Generator (version 2). Also in IOH https://github.com/IOHprofiler/IOHGNBG</td>
+      <td>Generalized Numerical Benchmark Generator (version 2). Also in IOH <a href="https://github.com/IOHprofiler/IOHGNBG">https://github.com/IOHprofiler/IOHGNBG</a></td>
       <td>suite; generator</td>
       <td>1</td>
       <td>scalable</td>
@@ -764,8 +764,8 @@
       <td>no</td>
       <td>no</td>
       <td>artificial</td>
-      <td><a href="https://dl.acm.org/doi/pdf/10.1145/3712255.3734271" target="_blank">https://dl.acm.org/doi/pdf/10.1145/3712255.3734271</a></td>
-      <td><a href="https://github.com/rohitsalgotra/GNBG-II" target="_blank">https://github.com/rohitsalgotra/GNBG-II</a></td>
+      <td><a href="https://dl.acm.org/doi/pdf/10.1145/3712255.3734271">https://dl.acm.org/doi/pdf/10.1145/3712255.3734271</a></td>
+      <td><a href="https://github.com/rohitsalgotra/GNBG-II">https://github.com/rohitsalgotra/GNBG-II</a></td>
     </tr>
     <tr>
       <td>GNBG</td>
@@ -779,8 +779,8 @@
       <td>no</td>
       <td>no</td>
       <td>artificial</td>
-      <td><a href="https://arxiv.org/abs/2312.07083" target="_blank">https://arxiv.org/abs/2312.07083</a></td>
-      <td><a href="https://github.com/Danial-Yazdani/GNBG-Generator" target="_blank">https://github.com/Danial-Yazdani/GNBG-Generator</a></td>
+      <td><a href="https://arxiv.org/abs/2312.07083">https://arxiv.org/abs/2312.07083</a></td>
+      <td><a href="https://github.com/Danial-Yazdani/GNBG-Generator">https://github.com/Danial-Yazdani/GNBG-Generator</a></td>
     </tr>
     <tr>
       <td>DynamicBinVal</td>
@@ -794,8 +794,8 @@
       <td>no</td>
       <td>no</td>
       <td>artificial</td>
-      <td><a href="https://arxiv.org/pdf/2404.15837" target="_blank">https://arxiv.org/pdf/2404.15837</a></td>
-      <td><a href="https://github.com/IOHprofiler/IOHexperimenter" target="_blank">https://github.com/IOHprofiler/IOHexperimenter</a></td>
+      <td><a href="https://arxiv.org/pdf/2404.15837">https://arxiv.org/pdf/2404.15837</a></td>
+      <td><a href="https://github.com/IOHprofiler/IOHexperimenter">https://github.com/IOHprofiler/IOHexperimenter</a></td>
     </tr>
     <tr>
       <td>PBO</td>
@@ -809,8 +809,8 @@
       <td>no</td>
       <td>no</td>
       <td>artificial</td>
-      <td><a href="https://dl.acm.org/doi/pdf/10.1145/3319619.3326810" target="_blank">https://dl.acm.org/doi/pdf/10.1145/3319619.3326810</a></td>
-      <td><a href="https://github.com/IOHprofiler/IOHexperimenter" target="_blank">https://github.com/IOHprofiler/IOHexperimenter</a></td>
+      <td><a href="https://dl.acm.org/doi/pdf/10.1145/3319619.3326810">https://dl.acm.org/doi/pdf/10.1145/3319619.3326810</a></td>
+      <td><a href="https://github.com/IOHprofiler/IOHexperimenter">https://github.com/IOHprofiler/IOHexperimenter</a></td>
     </tr>
     <tr>
       <td>W-model</td>
@@ -824,8 +824,8 @@
       <td>no</td>
       <td>no</td>
       <td>artificial</td>
-      <td><a href="https://dl.acm.org/doi/abs/10.1145/3205651.3208240?casa_token=S4U_Pi9f6MwAAAAA:U9ztNTPwmupT8K3GamWZfBL7-8fqjxPtr_kprv51vdwA-REsp0EyOFGa99BtbANb0XbqyrVg795hIw" target="_blank">https://dl.acm.org/doi/abs/10.1145/3205651.3208240?casa_token=S4U_Pi9f6MwAAAAA:U9ztNTPwmupT8K3GamWZfBL7-8fqjxPtr_kprv51vdwA-REsp0EyOFGa99BtbANb0XbqyrVg795hIw</a></td>
-      <td><a href="https://github.com/thomasWeise/BBDOB_W_Model" target="_blank">https://github.com/thomasWeise/BBDOB_W_Model</a></td>
+      <td><a href="https://dl.acm.org/doi/abs/10.1145/3205651.3208240?casa_token=S4U_Pi9f6MwAAAAA:U9ztNTPwmupT8K3GamWZfBL7-8fqjxPtr_kprv51vdwA-REsp0EyOFGa99BtbANb0XbqyrVg795hIw">https://dl.acm.org/doi/abs/10.1145/3205651.3208240?casa_token=S4U_Pi9f6MwAAAAA:U9ztNTPwmupT8K3GamWZfBL7-8fqjxPtr_kprv51vdwA-REsp0EyOFGa99BtbANb0XbqyrVg795hIw</a></td>
+      <td><a href="https://github.com/thomasWeise/BBDOB_W_Model">https://github.com/thomasWeise/BBDOB_W_Model</a></td>
     </tr>
     <tr>
       <td>Submodular Optimitzation</td>
@@ -839,12 +839,12 @@
       <td>no</td>
       <td>no</td>
       <td>artificial</td>
-      <td><a href="https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10254181" target="_blank">https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10254181</a></td>
-      <td><a href="https://github.com/IOHprofiler/IOHexperimenter" target="_blank">https://github.com/IOHprofiler/IOHexperimenter</a></td>
+      <td><a href="https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10254181">https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10254181</a></td>
+      <td><a href="https://github.com/IOHprofiler/IOHexperimenter">https://github.com/IOHprofiler/IOHexperimenter</a></td>
     </tr>
     <tr>
       <td>CEC2013</td>
-      <td>suite used for cec2013 competition. Also in IOH https://github.com/IOHprofiler/IOHexperimenter</td>
+      <td>suite used for cec2013 competition. Also in IOH <a href="https://github.com/IOHprofiler/IOHexperimenter">https://github.com/IOHprofiler/IOHexperimenter</a></td>
       <td>suite</td>
       <td>1</td>
       <td>scalable</td>
@@ -854,12 +854,12 @@
       <td>no</td>
       <td>no</td>
       <td>artificial</td>
-      <td><a href="https://peerj.com/articles/cs-2671/CEC2013.pdf" target="_blank">https://peerj.com/articles/cs-2671/CEC2013.pdf</a></td>
-      <td><a href="https://github.com/P-N-Suganthan/CEC2013" target="_blank">https://github.com/P-N-Suganthan/CEC2013</a></td>
+      <td><a href="https://peerj.com/articles/cs-2671/CEC2013.pdf">https://peerj.com/articles/cs-2671/CEC2013.pdf</a></td>
+      <td><a href="https://github.com/P-N-Suganthan/CEC2013">https://github.com/P-N-Suganthan/CEC2013</a></td>
     </tr>
     <tr>
       <td>CEC2022</td>
-      <td>suite used for cec2022 competition. Also in IOH https://github.com/IOHprofiler/IOHexperimenter</td>
+      <td>suite used for cec2022 competition. Also in IOH <a href="https://github.com/IOHprofiler/IOHexperimenter">https://github.com/IOHprofiler/IOHexperimenter</a></td>
       <td>suite</td>
       <td>1</td>
       <td>scalable</td>
@@ -869,8 +869,8 @@
       <td>no</td>
       <td>no</td>
       <td>artificial</td>
-      <td><a href="https://github.com/P-N-Suganthan/2022-SO-BO/blob/main/CEC2022%20TR.pdf" target="_blank">https://github.com/P-N-Suganthan/2022-SO-BO/blob/main/CEC2022%20TR.pdf</a></td>
-      <td><a href="https://github.com/P-N-Suganthan/2022-SO-BO" target="_blank">https://github.com/P-N-Suganthan/2022-SO-BO</a></td>
+      <td><a href="https://github.com/P-N-Suganthan/2022-SO-BO/blob/main/CEC2022%20TR.pdf">https://github.com/P-N-Suganthan/2022-SO-BO/blob/main/CEC2022%20TR.pdf</a></td>
+      <td><a href="https://github.com/P-N-Suganthan/2022-SO-BO">https://github.com/P-N-Suganthan/2022-SO-BO</a></td>
     </tr>
     <tr>
       <td>Onemax+Sphere / Zeromax+Sphere</td>
@@ -884,7 +884,7 @@
       <td>no</td>
       <td>no</td>
       <td>artificial</td>
-      <td><a href="https://doi.org/10.1145/3449726.3459521" target="_blank">https://doi.org/10.1145/3449726.3459521</a></td>
+      <td><a href="https://doi.org/10.1145/3449726.3459521">https://doi.org/10.1145/3449726.3459521</a></td>
       <td>None</td>
     </tr>
     <tr>
@@ -899,7 +899,7 @@
       <td>no</td>
       <td>no</td>
       <td>artificial</td>
-      <td><a href="https://doi.org/10.1145/3449726.3459521" target="_blank">https://doi.org/10.1145/3449726.3459521</a></td>
+      <td><a href="https://doi.org/10.1145/3449726.3459521">https://doi.org/10.1145/3449726.3459521</a></td>
       <td>None</td>
     </tr>
     <tr>
@@ -914,8 +914,203 @@
       <td>no</td>
       <td>no</td>
       <td>artificial</td>
-      <td><a href="https://doi.org/10.1145/3449726.3459521" target="_blank">https://doi.org/10.1145/3449726.3459521</a></td>
+      <td><a href="https://doi.org/10.1145/3449726.3459521">https://doi.org/10.1145/3449726.3459521</a></td>
       <td>None</td>
     </tr>
+    <tr>
+      <td>PorkchopPlotInterplanetaryTrajectory</td>
+      <td></td>
+      <td>suite</td>
+      <td>1</td>
+      <td>2</td>
+      <td>continuous</td>
+      <td>no</td>
+      <td>no</td>
+      <td>no</td>
+      <td>no</td>
+      <td>real-world</td>
+      <td><a href="https://doi.org/10.1109/CEC65147.2025.11042973">https://doi.org/10.1109/CEC65147.2025.11042973</a></td>
+      <td><a href="https://github.com/ShuaiqunPan/Transfer_Random_forests_BBOB_Real_world">https://github.com/ShuaiqunPan/Transfer_Random_forests_BBOB_Real_world</a></td>
+    </tr>
+    <tr>
+      <td>KinematicsRobotArm</td>
+      <td></td>
+      <td>suite</td>
+      <td>1</td>
+      <td>21</td>
+      <td>continuous</td>
+      <td>no</td>
+      <td>no</td>
+      <td>no</td>
+      <td>no</td>
+      <td>real-world</td>
+      <td><a href="https://doi.org/10.1023/A:1013258808932">https://doi.org/10.1023/A:1013258808932</a></td>
+      <td><a href="https://github.com/ShuaiqunPan/Transfer_Random_forests_BBOB_Real_world">https://github.com/ShuaiqunPan/Transfer_Random_forests_BBOB_Real_world</a></td>
+    </tr>
+    <tr>
+      <td>VehicleDynamics</td>
+      <td></td>
+      <td>suite</td>
+      <td>1</td>
+      <td>2</td>
+      <td>continuous</td>
+      <td>no</td>
+      <td>no</td>
+      <td>no</td>
+      <td>no</td>
+      <td>real-world</td>
+      <td><a href="https://www.scitepress.org/Papers/2023/121580/121580.pdf">https://www.scitepress.org/Papers/2023/121580/121580.pdf</a></td>
+      <td><a href="https://zenodo.org/records/8307853">https://zenodo.org/records/8307853</a></td>
+    </tr>
+    <tr>
+      <td>MECHBench</td>
+      <td>This is a set of problems with inspiration from Structural Mechanics Design Optimization. The suite comprises three physical models, from which the user may define different kind of problems which impact the final design output.</td>
+      <td>Problem Suite</td>
+      <td>1</td>
+      <td>scalable'</td>
+      <td>Continuous</td>
+      <td>yes</td>
+      <td>no</td>
+      <td>no</td>
+      <td>no</td>
+      <td>Real-World Application</td>
+      <td><a href="https://arxiv.org/abs/2511.10821">https://arxiv.org/abs/2511.10821</a></td>
+      <td><a href="https://github.com/BayesOptApp/MECHBench">https://github.com/BayesOptApp/MECHBench</a></td>
+    </tr>
+    <tr>
+      <td>EXPObench</td>
+      <td>Wind farm layout optimization, gas filter design, pipe shape optimization, hyperparameter tuning, and hospital simulation</td>
+      <td>Problem Suite</td>
+      <td>1</td>
+      <td>10 to 135</td>
+      <td>Continuous, Integer, Categorical, Conditional</td>
+      <td>yes</td>
+      <td>no</td>
+      <td>yes</td>
+      <td>no</td>
+      <td>Real-World Application</td>
+      <td><a href="https://doi.org/10.1016/j.asoc.2023.110744">https://doi.org/10.1016/j.asoc.2023.110744</a></td>
+      <td><a href="https://github.com/AlgTUDelft/ExpensiveOptimBenchmark">https://github.com/AlgTUDelft/ExpensiveOptimBenchmark</a></td>
+    </tr>
+    <tr>
+      <td>Gasoline direct injection engine design</td>
+      <td>A multi-objective optimization problem seeking to minimize fuel consumption and NOx emissions over a two-minute dynamic duty cycle, subject to five constraints (turbine inlet temperature, number of knock occurrences, peak cylinder pressure, peak cylinder pressure rise, total work). Seven decision variables are defined: four define the hardware choices of cylinder compression ratio, turbo machinery and EGR cooler sizing; three relate to control variables that parameterise the engine control logic.</td>
+      <td>Single Problem</td>
+      <td>2</td>
+      <td>7</td>
+      <td>Continuous, Ordinal</td>
+      <td>yes</td>
+      <td>no</td>
+      <td>no</td>
+      <td>yes</td>
+      <td>Real-World Application</td>
+      <td></td>
+      <td><a href="https://doi.org/10.1016/j.ejor.2022.08.032">https://doi.org/10.1016/j.ejor.2022.08.032</a></td>
+    </tr>
+    <tr>
+      <td>BEACON</td>
+      <td>Generator for bi-objective benchmark problems with explicitly controlled correlations in continuous spaces.</td>
+      <td>Generator</td>
+      <td>2</td>
+      <td>scalable</td>
+      <td>Continuous</td>
+      <td>no</td>
+      <td>no</td>
+      <td>no</td>
+      <td>no</td>
+      <td>Artificially Generated</td>
+      <td><a href="https://dl.acm.org/doi/10.1145/3712255.3734303">https://dl.acm.org/doi/10.1145/3712255.3734303</a></td>
+      <td><a href="https://github.com/Stebbet/BEACON/">https://github.com/Stebbet/BEACON/</a></td>
+    </tr>
+    <tr>
+      <td>TulipaEnergy</td>
+      <td>Determine the optimal investment and operation decisions  for different types of assets in the energy system (production, consumption, conversion, storage, and transport), while minimizing loss of load.</td>
+      <td>Problem Suite</td>
+      <td>1</td>
+      <td>scalable</td>
+      <td>Continuous</td>
+      <td>yes</td>
+      <td>no</td>
+      <td>yes</td>
+      <td>yes</td>
+      <td>Real-World Application</td>
+      <td><a href="https://tulipaenergy.github.io/TulipaEnergyModel.jl/stable/40-scientific-foundation/45-scientific-references">https://tulipaenergy.github.io/TulipaEnergyModel.jl/stable/40-scientific-foundation/45-scientific-references</a></td>
+      <td><a href="https://tulipaenergy.github.io/TulipaEnergyModel.jl/stable/">https://tulipaenergy.github.io/TulipaEnergyModel.jl/stable/</a></td>
+    </tr>
+    <tr>
+      <td>ATO</td>
+      <td>Parameters of the Modules of the Automatic Train Operation should be optimized. The parameters are continuous with different ranges. There are two objectives (minimizing energy consumption, minimizing driving duration.</td>
+      <td>Single Problem</td>
+      <td>2</td>
+      <td>10</td>
+      <td>Continuous</td>
+      <td>no</td>
+      <td>no</td>
+      <td>no</td>
+      <td>no</td>
+      <td>Real-World Application</td>
+      <td></td>
+      <td>-</td>
+    </tr>
+    <tr>
+      <td>Brachytherapy treatment planning</td>
+      <td>Treatment planning for internal radiation therapy</td>
+      <td>Problem Suite</td>
+      <td>2-3</td>
+      <td>100-500</td>
+      <td>Continuous</td>
+      <td>yes</td>
+      <td>no</td>
+      <td>no</td>
+      <td>yes</td>
+      <td>Real-World Application</td>
+      <td><a href="https://www.sciencedirect.com/science/article/pii/S1538472123016781">https://www.sciencedirect.com/science/article/pii/S1538472123016781</a></td>
+      <td></td>
+    </tr>
+    <tr>
+      <td>FleetOpt</td>
+      <td>Healthcare organisation in the UK provided data about their current fleet of vehicles to conduct non-emergency heathcare trips in the Argyll and Bute region of Scotland, UK. They also provided historical data about the trips the vehicles took and about the bases which the vehicles return to. The aim is to reduce the existing fleet of vehicles while still ensuring all trips can be covered. Moving a vehicle from one base to another to help cover trips is OK as long as the original base can still cover its trips. Link to paper with more details: <a href="https://dl.acm.org/doi/abs/10.1145/3638530.3664137">https://dl.acm.org/doi/abs/10.1145/3638530.3664137</a></td>
+      <td>Single Problem</td>
+      <td>1</td>
+      <td>Upper level: 54; lower level: 13208</td>
+      <td>Integer</td>
+      <td>yes</td>
+      <td>no</td>
+      <td>no</td>
+      <td>no</td>
+      <td>Real-World Application</td>
+      <td><a href="https://dl.acm.org/doi/abs/10.1145/3638530.3664137">https://dl.acm.org/doi/abs/10.1145/3638530.3664137</a></td>
+      <td>Not public: was done for real client with their private data</td>
+    </tr>
+    <tr>
+      <td>Building spatial design</td>
+      <td>Optimise the spatial layout of a building to: minimise energy consumption for climate control, and minimise the strain on the structure</td>
+      <td>Single Problem</td>
+      <td>2</td>
+      <td>scalable depending on problem size (e.g. 90 for)</td>
+      <td>Continuous, Boolean</td>
+      <td>yes</td>
+      <td>no</td>
+      <td>no</td>
+      <td>no</td>
+      <td>Real-World Application</td>
+      <td><a href="https://hdl.handle.net/1887/81789">https://hdl.handle.net/1887/81789</a></td>
+      <td><a href="https://github.com/TUe-excellent-buildings/BSO-toolbox">https://github.com/TUe-excellent-buildings/BSO-toolbox</a></td>
+    </tr>
+    <tr>
+      <td>Electric Motor Design Optimization</td>
+      <td>The goal is to find a design of a synchronous electric motor for power steering systems that minimizes costs and satisfies all constraints.</td>
+      <td>Single Problem</td>
+      <td>1</td>
+      <td>13</td>
+      <td>Continuous, Integer</td>
+      <td>yes</td>
+      <td>no</td>
+      <td>yes</td>
+      <td>no</td>
+      <td>Real-World Application</td>
+      <td><a href="https://dis.ijs.si/tea/Publications/Tusar23Multistep.pdf">https://dis.ijs.si/tea/Publications/Tusar23Multistep.pdf</a> (paper in Slovene)</td>
+      <td>Implementation not freely available</td>
+    </tr>
   </tbody>
 <tfoot><tr><th>name</th> <th>textual description</th> <th>suite/generator/single</th> <th>objectives</th> <th>dimensionality</th> <th>variable type</th> <th>constraints</th> <th>dynamic</th> <th>noise</th> <th>multi-fidelity</th> <th>source (real-world/artificial)</th> <th>reference</th> <th>implementation</th></tr> </tfoot></table>
\ No newline at end of file
diff --git a/problems.yaml b/problems.yaml
index 8d3a3c0..3cfb557 100644
--- a/problems.yaml
+++ b/problems.yaml
@@ -858,3 +858,415 @@
   implementation:
   source (real-world/artificial): 'artificial'
   textual description: ''
+- name: PorkchopPlotInterplanetaryTrajectory
+  suite/generator/single: suite
+  objectives: '1'
+  dimensionality: 2
+  variable type: continuous
+  constraints: 'no'
+  dynamic: 'no'
+  noise: 'no'
+  multimodal: 'yes'
+  multi-fidelity: 'no'
+  reference: https://doi.org/10.1109/CEC65147.2025.11042973
+  implementation: https://github.com/ShuaiqunPan/Transfer_Random_forests_BBOB_Real_world
+  source (real-world/artificial): 'real-world'
+  textual description: ''
+- name: KinematicsRobotArm
+  suite/generator/single: suite
+  objectives: '1'
+  dimensionality: 21
+  variable type: continuous
+  constraints: 'no'
+  dynamic: 'no'
+  noise: 'no'
+  multimodal: 'no'
+  multi-fidelity: 'no'
+  reference: https://doi.org/10.1023/A:1013258808932
+  implementation: https://github.com/ShuaiqunPan/Transfer_Random_forests_BBOB_Real_world
+  source (real-world/artificial): 'real-world'
+  textual description: ''
+- name:  VehicleDynamics
+  suite/generator/single: suite
+  objectives: '1'
+  dimensionality: 2
+  variable type: continuous
+  constraints: 'no'
+  dynamic: 'no'
+  noise: 'no'
+  multimodal: 'yes'
+  multi-fidelity: 'no'
+  reference: https://www.scitepress.org/Papers/2023/121580/121580.pdf
+  implementation: https://zenodo.org/records/8307853
+  source (real-world/artificial): 'real-world'
+  textual description: ''
+- name: MECHBench
+  suite/generator/single: Problem Suite
+  variable type: Continuous
+  dimensionality: scalable'
+  objectives: '1'
+  constraints: 'yes'
+  dynamic: 'no'
+  noise: 'no'
+  multimodal: 'yes'
+  multi-fidelity: 'no'
+  source (real-world/artificial): Real-World Application
+  implementation: https://github.com/BayesOptApp/MECHBench
+  textual description: This is a set of problems with inspiration from Structural
+    Mechanics Design Optimization. The suite comprises three physical models, from
+    which the user may define different kind of problems which impact the final design
+    output.
+  reference: https://arxiv.org/abs/2511.10821
+  other info:
+    name: null
+    partial evaluations: Not Present
+    full name: MECHBench
+    constraint properties: Hard Constraints
+    number of constraints: 1 or 2
+    type of dynamicism: ''
+    form of noise model: ''
+    type of noise space: ''
+    other noise properties: ''
+    description of multimodality: Unstructured or non isotropic multimodality
+    key challenges / characteristics: Embeds physical simulations and is flexible
+      and modular
+    scientific motivation: Bridge the black-box optimization techniques to a Mechanical
+      Design Problem which require these kinds of algorithms
+    limitations: The models do not include fracture or damage mechanics, just plasticity.
+    implementation languages: Python
+    links to implementations: https://github.com/BayesOptApp/MECHBench
+    approximate evaluation time: Times -> from 1 minute to 7 minutes
+    links to usage examples: ''
+    general: ''
+- name: EXPObench
+  suite/generator/single: Problem Suite
+  variable type: Continuous, Integer, Categorical, Conditional
+  dimensionality: 10 to 135
+  objectives: '1'
+  constraints: 'yes'
+  dynamic: 'no'
+  noise: 'yes'
+  multimodal: Unknown
+  multi-fidelity: 'no'
+  source (real-world/artificial): Real-World Application
+  implementation: https://github.com/AlgTUDelft/ExpensiveOptimBenchmark
+  textual description: Wind farm layout optimization, gas filter design, pipe shape
+    optimization, hyperparameter tuning, and hospital simulation
+  reference: https://doi.org/10.1016/j.asoc.2023.110744
+  other info:
+    name: null
+    partial evaluations: Not Present
+    full name: EXPensive Optimization benchmark library
+    constraint properties: Hard Constraints, Soft Constraints, Box Constraints, only
+      box constraints implemented, others appear as penalty in objective
+    number of constraints: 2 per variable (box), other constraints unknown (simulator
+      fails)
+    type of dynamicism: ''
+    form of noise model: real-life (unknown)
+    type of noise space: Observational
+    other noise properties: ''
+    description of multimodality: ''
+    key challenges / characteristics: Expensive objectives
+    scientific motivation: Address the lack of real-life expensive benchmarks
+    limitations: single-objective only, constraints are handled naively (penalty in
+      objective), no parallelization
+    implementation languages: Python
+    links to implementations: https://github.com/AlgTUDelft/ExpensiveOptimBenchmark
+    approximate evaluation time: 2 to 80 seconds
+    links to usage examples: ''
+    general: ''
+- name: Gasoline direct injection engine design
+  suite/generator/single: Single Problem
+  variable type: Continuous, Ordinal
+  dimensionality: '7'
+  objectives: '2'
+  constraints: 'yes'
+  dynamic: 'no'
+  noise: 'no'
+  multimodal: Unknown
+  multi-fidelity: 'yes'
+  source (real-world/artificial): Real-World Application
+  implementation: https://doi.org/10.1016/j.ejor.2022.08.032
+  textual description: 'A multi-objective optimization problem seeking to minimize
+    fuel consumption and NOx emissions over a two-minute dynamic duty cycle, subject
+    to five constraints (turbine inlet temperature, number of knock occurrences, peak
+    cylinder pressure, peak cylinder pressure rise, total work). Seven decision variables
+    are defined: four define the hardware choices of cylinder compression ratio, turbo
+    machinery and EGR cooler sizing; three relate to control variables that parameterise
+    the engine control logic.'
+  reference: ''
+  other info:
+    name: null
+    partial evaluations: Unknown
+    full name: ''
+    constraint properties: Hard Constraints, Soft Constraints
+    number of constraints: '5'
+    type of dynamicism: ''
+    form of noise model: ''
+    type of noise space: ''
+    other noise properties: ''
+    description of multimodality: ''
+    key challenges / characteristics: Expensive
+    scientific motivation: ''
+    limitations: Proprietary
+    implementation languages: Matlab Simulink and Wave RT co-simulation
+    links to implementations: ''
+    approximate evaluation time: ''
+    links to usage examples: ''
+    general: ''
+- name: BEACON
+  suite/generator/single: Generator
+  variable type: Continuous
+  dimensionality: scalable
+  objectives: '2'
+  constraints: 'no'
+  dynamic: 'no'
+  noise: 'no'
+  multimodal: 'yes'
+  multi-fidelity: 'no'
+  source (real-world/artificial): Artificially Generated
+  implementation: https://github.com/Stebbet/BEACON/
+  textual description: Generator for bi-objective benchmark problems with explicitly
+    controlled correlations in continuous spaces.
+  reference: https://dl.acm.org/doi/10.1145/3712255.3734303
+  other info:
+    name: null
+    partial evaluations: Not Present
+    full name: Continuous Bi-objective Benchmark problems with Explicit Adjustable
+      COrrelatioN control
+    constraint properties: Box Constraints
+    number of constraints: '0'
+    type of dynamicism: ''
+    form of noise model: ''
+    type of noise space: ''
+    other noise properties: ''
+    description of multimodality: Random
+    key challenges / characteristics: Multimodal, different correlations among objectives
+    scientific motivation: Controlled correlation among objectives
+    limitations: No analytical Pareto front, only bi-objective
+    implementation languages: Python
+    links to implementations: https://github.com/Stebbet/BEACON/tree/main
+    approximate evaluation time: Negligible
+    links to usage examples: ''
+    general: ''
+- name: TulipaEnergy
+  suite/generator/single: Problem Suite
+  variable type: Continuous
+  dimensionality: scalable
+  objectives: '1'
+  constraints: 'yes'
+  dynamic: 'no'
+  noise: 'yes'
+  multimodal: 'no'
+  multi-fidelity: 'yes'
+  source (real-world/artificial): Real-World Application
+  implementation: https://tulipaenergy.github.io/TulipaEnergyModel.jl/stable/
+  textual description: Determine the optimal investment and operation decisions  for
+    different types of assets in the energy system (production, consumption, conversion,
+    storage, and transport), while minimizing loss of load.
+  reference: https://tulipaenergy.github.io/TulipaEnergyModel.jl/stable/40-scientific-foundation/45-scientific-references
+  other info:
+    name: null
+    partial evaluations: Unknown
+    full name: TulipaEnergyModel.jl
+    constraint properties: Hard Constraints, Soft Constraints
+    number of constraints: millions
+    type of dynamicism: none
+    form of noise model: "depends on input \u2014 still working on stochastic inputs"
+    type of noise space: Parameter
+    other noise properties: ''
+    description of multimodality: ''
+    key challenges / characteristics: modeled as a potentially very large linear program,
+      different fidelities possible
+    scientific motivation: new techniques for solving large whitebox linear optimization
+      problems
+    limitations: not yet stochastic
+    implementation languages: Julia / JMP
+    links to implementations: https://github.com/TulipaEnergy/TulipaEnergyModel.jl
+    approximate evaluation time: from minutes to hours
+    links to usage examples: https://github.com/TulipaEnergy/Tulipa-OBZ-CaseStudy
+    general: ''
+- name: ATO
+  suite/generator/single: Single Problem
+  variable type: Continuous
+  dimensionality: '10'
+  objectives: '2'
+  constraints: 'no'
+  dynamic: 'no'
+  noise: 'no'
+  multimodal: 'no'
+  multi-fidelity: 'no'
+  source (real-world/artificial): Real-World Application
+  implementation: '-'
+  textual description: Parameters of the Modules of the Automatic Train Operation
+    should be optimized. The parameters are continuous with different ranges. There
+    are two objectives (minimizing energy consumption, minimizing driving duration.
+  reference: ''
+  other info:
+    name: null
+    partial evaluations: Not Present
+    full name: ''
+    constraint properties: ''
+    number of constraints: ''
+    type of dynamicism: ''
+    form of noise model: ''
+    type of noise space: ''
+    other noise properties: ''
+    description of multimodality: ''
+    key challenges / characteristics: ''
+    scientific motivation: ''
+    limitations: ''
+    implementation languages: ''
+    links to implementations: ''
+    approximate evaluation time: ''
+    links to usage examples: ''
+    general: ''
+- name: Brachytherapy treatment planning
+  suite/generator/single: Problem Suite
+  variable type: Continuous
+  dimensionality: 100-500
+  objectives: 2-3
+  constraints: 'yes'
+  dynamic: 'no'
+  noise: 'no'
+  multimodal: 'yes'
+  multi-fidelity: 'yes'
+  source (real-world/artificial): Real-World Application
+  implementation: ''
+  textual description: Treatment planning for internal radiation therapy
+  reference: https://www.sciencedirect.com/science/article/pii/S1538472123016781
+  other info:
+    name: null
+    partial evaluations: Present
+    full name: Brachytherapy treatment planning
+    constraint properties: Hard Constraints
+    number of constraints: scalable
+    type of dynamicism: ''
+    form of noise model: ''
+    type of noise space: ''
+    other noise properties: ''
+    description of multimodality: ''
+    key challenges / characteristics: Multi-objective; aggregated objectives
+    scientific motivation: ''
+    limitations: No public source code
+    implementation languages: ''
+    links to implementations: ''
+    approximate evaluation time: ''
+    links to usage examples: ''
+    general: ''
+- name: FleetOpt
+  suite/generator/single: Single Problem
+  variable type: Integer
+  dimensionality: 'Upper level: 54; lower level: 13208'
+  objectives: '1'
+  constraints: 'yes'
+  dynamic: 'no'
+  noise: 'no'
+  multimodal: Unknown
+  multi-fidelity: 'no'
+  source (real-world/artificial): Real-World Application
+  implementation: 'Not public: was done for real client with their private data'
+  textual description: 'Healthcare organisation in the UK provided data about their
+    current fleet of vehicles to conduct non-emergency heathcare trips in the Argyll
+    and Bute region of Scotland, UK. They also provided historical data about the
+    trips the vehicles took and about the bases which the vehicles return to. The
+    aim is to reduce the existing fleet of vehicles while still ensuring all trips
+    can be covered. Moving a vehicle from one base to another to help cover trips
+    is OK as long as the original base can still cover its trips. Link to paper with
+    more details: https://dl.acm.org/doi/abs/10.1145/3638530.3664137'
+  reference: 'https://dl.acm.org/doi/abs/10.1145/3638530.3664137'
+  other info:
+    name: null
+    partial evaluations: Present
+    full name: ''
+    constraint properties: ''
+    number of constraints: ''
+    type of dynamicism: ''
+    form of noise model: ''
+    type of noise space: ''
+    other noise properties: ''
+    description of multimodality: ''
+    key challenges / characteristics: ''
+    scientific motivation: ''
+    limitations: ''
+    implementation languages: ''
+    links to implementations: ''
+    approximate evaluation time: ''
+    links to usage examples: ''
+    general: ''
+- name: Building spatial design
+  suite/generator/single: Single Problem
+  variable type: Continuous, Boolean
+  dimensionality: scalable depending on problem size (e.g. 90 for)
+  objectives: '2'
+  constraints: 'yes'
+  dynamic: 'no'
+  noise: 'no'
+  multimodal: Unknown
+  multi-fidelity: 'no'
+  source (real-world/artificial): Real-World Application
+  implementation: https://github.com/TUe-excellent-buildings/BSO-toolbox
+  textual description: 'Optimise the spatial layout of a building to: minimise energy
+    consumption for climate control, and minimise the strain on the structure'
+  reference: https://hdl.handle.net/1887/81789
+  other info:
+    name: null
+    partial evaluations: Not Present
+    full name: Building spatial design
+    constraint properties: Hard Constraints, Box Constraints, Permutation Constraints
+    number of constraints: 2065 (as example, depends on problem size)
+    type of dynamicism: ''
+    form of noise model: ''
+    type of noise space: ''
+    other noise properties: ''
+    description of multimodality: ''
+    key challenges / characteristics: Many hard constraints (simulator cannot evaluate
+      the solution if these are violated); Mixed-variable search space (continuous
+      + binary); Multiple objectives; (Somewhat) expensive solution evaluations
+    scientific motivation: ''
+    limitations: ''
+    implementation languages: C++
+    links to implementations: https://github.com/TUe-excellent-buildings/BSO-toolbox
+    approximate evaluation time: Roughly 1 second per evaluation for the smallest
+      considered design, and roughly 40 seconds for the larger designs we considered.
+      (Even the larger designs we considered are still relatively small for the considered
+      problem.)
+    links to usage examples: ''
+    general: ''
+- name: Electric Motor Design Optimization
+  suite/generator/single: Single Problem
+  variable type: Continuous, Integer
+  dimensionality: '13'
+  objectives: '1'
+  constraints: 'yes'
+  dynamic: 'no'
+  noise: 'yes'
+  multimodal: 'yes'
+  multi-fidelity: 'no'
+  source (real-world/artificial): Real-World Application
+  implementation: Implementation not freely available
+  textual description: The goal is to find a design of a synchronous electric motor
+    for power steering systems that minimizes costs and satisfies all constraints.
+  reference: https://dis.ijs.si/tea/Publications/Tusar23Multistep.pdf (paper in Slovene)
+  other info:
+    name: null
+    partial evaluations: Not Present
+    full name: Electric Motor Design Optimization
+    constraint properties: Hard Constraints, Soft Constraints, Box Constraints
+    number of constraints: '12'
+    type of dynamicism: ''
+    form of noise model: ''
+    type of noise space: ''
+    other noise properties: ''
+    description of multimodality: Constraints are multimodal
+    key challenges / characteristics: Time-consuming solution evaluation, highly-constrained
+      problem
+    scientific motivation: Challenging to find good solutions in a limited time
+    limitations: 'Unavailability, even if available, it wouldn''t be helpful to use
+      for benchmarking due taking a long time to evaluate a single solution '
+    implementation languages: Python
+    links to implementations: Implementation not freely available
+    approximate evaluation time: 8 minutes
+    links to usage examples: ''
+    general: This is not an available problem, but could be interesting to show to
+      researchers which difficulties appear in real-world problems
diff --git a/utils/new_problem.yaml b/utils/new_problem.yaml
index 9d9fa23..2c300e1 100644
--- a/utils/new_problem.yaml
+++ b/utils/new_problem.yaml
@@ -1,6 +1,6 @@
 - name: template
   suite/generator/single: suite
-  objectives: '1'
+  objectives: '2'
   dimensionality: scalable
   variable type: continuous
   constraints: 'no'
diff --git a/yaml_to_html.py b/yaml_to_html.py
index df79580..a9a219f 100755
--- a/yaml_to_html.py
+++ b/yaml_to_html.py
@@ -4,6 +4,22 @@
 import yaml
 import shutil
 
+import re
+
+URL_RE = re.compile(r'\b((?:https?://|www\.)[^\s<>"\']+)', re.IGNORECASE)
+
+
+def linkify_cell(value):
+    if not isinstance(value, str):
+        return value
+
+    def repl(m):
+        url = m.group(1)
+        href = url if url.lower().startswith(("http://", "https://")) else f"https://{url}"
+        return f'<a href="{href}">{url}</a>'
+
+    return URL_RE.sub(repl, value)
+
 yaml_file = "problems.yaml"
 
 html_dir = "docs/"
@@ -37,8 +53,11 @@
     columns = default_columns
     data = data[columns]
 
+data = data.map(linkify_cell)
+
 # Generate plain table
-table = data.to_html(render_links=True,
+table = data.to_html(render_links=False,
+                     escape=False,  # Don't escape HTML in cells (to allow links)
                      index=False,
                      table_id="problems",
                      classes=["display compact", "display", "styled-table"],  # Set display style