Particle swarm with equilibrium strategy of selection for multi-objective optimization

Yujia Wang and Yupu Yang

European Journal of Operational Research, 2010, vol. 200, issue 1, pages 187-197

Abstract: A new ranking scheme based on equilibrium strategy of selection is proposed for multi-objective particle swarm optimization (MOPSO), and the preference ordering is used to identify the "best compromise" in the ranking stage. This scheme increases the selective pressure, especially when the number of objectives is very large. The proposed algorithm has been compared with other multi-objective evolutionary algorithms (MOEAs). The experimental results indicate that our algorithm produces better convergence performance.

Keywords: Particle; swarm; Equilibrium; strategy; of; selection; Multi-objective; optimization; Preference; ordering (search for similar items in EconPapers)
Date: 2010

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Persistent link: http://EconPapers.repec.org/RePEc:eee:ejores:v:200:y:2010:i:1:p:187-197

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European Journal of Operational Research is edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati

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