Multi-Objective Self-Organizing Migrating Algorithm: Sensitivity on Controlling Parameters
Alternative metrics PlumXhttp://hdl.handle.net/11012/36851
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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.
Document typePeer reviewed
Document versionFinal PDF
SourceRadioengineering. 2013, vol. 22, č. 1, s. 296-308. ISSN 1210-2512
- 2013/1