Multi-Population Multi-Objective Cultural Algorithm

Abstract:

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In existing multi-population multi-objective cultural algorithms, information are exchanged among sub-populations by individuals. However, migrated individuals can not reflect the evolution information enough, which limits the evolution performance.In order to enhance the migration efficiency, a novel multi-population multi-objective cultural algorithm adopting knowledge migration is proposed. Implicit knowledge extracted from the evolution process of each sub-population directly reflects the information about dominant search space. By migrating the knowledge among sub-populations at the constant interval, the algorithm realizes more effective interaction with less communication cost. Taken benchmark functions as the examples, simulation results indicate that the algorithm can effectively obtain the Pareto-optimal sets of multi-objective optimization problems. The distribution performance is also improved.

Info:

Periodical:

Advanced Materials Research (Volumes 156-157)

Edited by:

Jingtao Han, Zhengyi Jiang and Sihai Jiao

Pages:

52-55

DOI:

10.4028/www.scientific.net/AMR.156-157.52

Citation:

Y. N. Guo et al., "Multi-Population Multi-Objective Cultural Algorithm", Advanced Materials Research, Vols. 156-157, pp. 52-55, 2011

Online since:

October 2010

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Price:

$35.00

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