A competitive and cooperative co-evolutionary approach to multi-objective particle swarm optimization algorithm design

Multi-objective particle swarm optimization (MOPSO) is an optimization technique inspired by bird flocking, which has been steadily gaining attention from the research community because of its high convergence speed. On the other hand, in the face of increasing complexity and dimensionality of today...

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Veröffentlicht in:	European journal of operational research Jg. 202; H. 1; S. 42 - 54
Hauptverfasser:	Goh, C.K., Tan, K.C., Liu, D.S., Chiam, S.C.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 01.04.2010 Elsevier Elsevier Sequoia S.A
Schriftenreihe:	European Journal of Operational Research
Schlagworte:	Applied sciences Competition Competitive–cooperative co-evolution Cooperation Decision theory. Utility theory Efficiency Exact sciences and technology Multi-objective optimization Multi-objective optimization Particle swarm optimization Competitive-cooperative co-evolution Operational research and scientific management Operational research. Management science Optimization algorithms Optimization techniques Particle swarm optimization Simulation Studies Particle swarm optimization Multi-objective optimization Competitive–cooperative co-evolution Dimensionality Evolutionary algorithm Multiobjective programming Evolution equation Modeling Convergence speed Vertebrata Competitive-cooperative co-evolution High speed Problem solving Swarm intelligence Metric Aves
ISSN:	0377-2217, 1872-6860
Online-Zugang:	Volltext
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