Result Details
Multi-Objective Self-Organizing Migrating Algorithm: Sensitivity on Controlling Parameters
Raida Zbyněk, prof. Dr. Ing., UREL (FEEC)
Dřínovský Jiří, Ing., Ph.D., UREL (FEEC)
In this paper, we investigate the sensitivity of a novel Multi-Objective Self-Organizing Migrating Algorithm (MOSOMA) on setting its control parameters. Usually, efficiency and accuracy of searching for a solution depends on the settings of a used stochastic algorithm, because multi-objective optimization problems are highly non-linear. In the paper, the sensitivity analysis is performed exploiting a large number of benchmark problems having different properties (the number of optimized parameters, the shape of a Pareto front, etc.). The quality of solutions revealed by MOSOMA is evaluated in terms of a generational distance, a spread and a hyper-volume error. Recommendations for proper settings of the algorithm are derived: These recommendations should help a user to set the algorithm for any multi-objective task without prior knowledge about the solved problem.
MOSOMA, sensitivity, control parameters, multi-objective optimization
@article{BUT99185,
author="Petr {Kadlec} and Zbyněk {Raida} and Jiří {Dřínovský}",
title="Multi-Objective Self-Organizing Migrating Algorithm: Sensitivity on Controlling Parameters",
journal="Radioengineering",
year="2013",
volume="22",
number="1",
pages="296--308",
issn="1210-2512",
url="http://radioeng.cz/fulltexts/2013/13_01_0296_0308.pdf"
}