A new dynamic particle swarm optimizer

被引:0
作者
Zheng, Binbin [1 ]
Li, Yuanxiang
Shen, Xianjun
Zheng, Bojin
机构
[1] Wuhan Univ, State Key Lab Software Engn, Wuhan 430072, Peoples R China
[2] S Cent Univ Nationalities, Coll Comp Sci, Wuhan 430074, Peoples R China
来源
SIMULATED EVOLUTION AND LEARNING, PROCEEDINGS | 2006年 / 4247卷
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:481 / 488
页数:8
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