Improved Multi-Objective Diversity Control Oriented Genetic Algorithm

Autor:	Theera Piroonratana, Nachol Chaiyaratana
Rok vydání:	2006
Předmět:	symbols.namesake Mathematical optimization Chromosome (genetic algorithm) Genetic algorithm Sorting symbols Pareto principle Evolutionary algorithm ComputingMilieux_LEGALASPECTSOFCOMPUTING Pareto distribution Genetic operator Multi-objective optimization Mathematics
Zdroj:	Artificial Intelligence and Soft Computing – ICAISC 2006 ISBN: 9783540357483 ICAISC
DOI:	10.1007/11785231_46
Popis:	This paper presents an improved multi-objective diversity control oriented genetic algorithm (MODCGA-II). The improvement includes the introduction of an objective-domain diversity control operator, which is chromosome representation independent, and a solution archive. The performance comparison between the MODCGA-II, a non-dominated sorting genetic algorithm II (NSGA-II) and an improved strength Pareto evolutionary algorithm (SPEA-II) is carried out where different two-objective benchmark problems with specific multi-objective characteristics are utilised. The results indicate that the MODCGA-II solutions are better than the solutions generated by the NSGA-II and SPEA-II in terms of the closeness to the true Pareto optimal solutions and the uniformity of solution distribution along the Pareto front.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::98399cc97846d4cc29dd55f6824c6bb0 https://doi.org/10.1007/11785231_46 Zobrazit plný text záznamu