A Novel Multi-Objective Self-Organizing Migrating Algorithm
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In the paper, a novel stochastic Multi-Objective Self Organizing Migrating Algorithm (MOSOMA) is introduced. For the search of optima, MOSOMA employs a migration technique used in a single-objective Self Organizing Migrating Algorithm (SOMA). In order to obtain a uniform distribution of Pareto optimal solutions, a novel technique considering Euclidian distances among solutions is introduced. MOSOMA performance was tested on benchmark problems and selected electromagnetic structures. MOSOMA performance was compared with the performance of the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and the Strength Pareto Evolutionary Algorithm 2 (SPEA2). MOSOMA excels in the uniform distribution of solutions and their completeness.
KeywordsMulti-objective optimization, self-organizing migrating algorithm, Pareto front of optimal solutions
Document typePeer reviewed
Document versionFinal PDF
SourceRadioengineering. 2011, vol. 20, č. 4, s. 804-816. ISSN 1210-2512
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