Multiobjective Optimization Test Environment

Tests algorithms on multiobjective optimization problems and outputs data along with visuals and accuracy profiles
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Aggiornato 17 giu 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.

Cita come

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

Compatibilità della release di MATLAB
Creato con R2019a
Compatibile con qualsiasi release
Compatibilità della piattaforma
Windows macOS Linux

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Versione Pubblicato Note della release
1.0

Per visualizzare o segnalare problemi su questo componente aggiuntivo di GitHub, visita GitHub Repository.
Per visualizzare o segnalare problemi su questo componente aggiuntivo di GitHub, visita GitHub Repository.