Multiobjective Optimization Test Environment
Tests algorithms on multiobjective optimization problems and outputs data along with visuals and accuracy profiles
https://github.com/pat2017b/Multiobjective-Optimization-Test-Environment
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The Multiobjective Optimization Test Environment allows the user to test algorithms on multiobjective optimization problems. This code was produced for my master's thesis named Multiobjective Nelder-Mead Algorithm Using a Mesh-Map of Weighted Sums. Features of the test environment include:
ALGORITHMS:
Random Search
Grid Search
MOPSO
NSGA-II
MNM-MeshMap
TEST SETS:
Wikipedia problems
DTLZ problems
Randomly generated problems (Quadratics and Sine Polynomials)
User-defined problems (Input your own problem)
METRICS:
Hypervolume
Contribution
Epsilon Indicator
VISUALS:
Algorithm results on individual problems
Accuracy profiles for larger data sets
OTHER:
Comma-Separated Values (CSV) file of data summary
Enjoy.
Cite As
Patrick Nadeau (2026). Multiobjective Optimization Test Environment (https://github.com/pat2017b/Multiobjective-Optimization-Test-Environment/releases/tag/v1.0), GitHub. Retrieved .
Acknowledgements
General Information
- Version 1.0 (517 KB)
-
View License on GitHub
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.0 |
