A new dynamic particle swarm optimizer

Authors:
Binbin Zheng;Yuanxiang Li;Xianjun Shen;Bojin Zheng
Affiliations:
State Key Lab. of Software Engineering, Wuhan University, Wuhan, China;State Key Lab. of Software Engineering, Wuhan University, Wuhan, China;State Key Lab. of Software Engineering, Wuhan University, Wuhan, China;College of Computer Science, South-Central University For Nationalities, Wuhan, China
Venue:
SEAL'06 Proceedings of the 6th international conference on Simulated Evolution And Learning
Year:
2006

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Abstract

This paper presents a new optimization model— Dynamic Particle Swarm Optimizer (DPSO). A new acceptance rule that based on the principle of minimal free energy from the statistical mechanics is introduced to the standard particle swarm optimizer. A definition of the entropy of the particle system is given. Then the law of entropy increment is applied to control the algorithm. Simulations have been done to illustrate the significant and effective impact of this new rule on the particle swarm optimizer.