Multiobjective Optimization Test Environment

Tests algorithms on multiobjective optimization problems and outputs data along with visuals and accuracy profiles
339 Downloads
Updated 17 Jun 2020

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 (2024). Multiobjective Optimization Test Environment (https://github.com/pat2017b/Multiobjective-Optimization-Test-Environment/releases/tag/v1.0), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2019a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
1.0

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.