Enforced Mutation to Enhancing the Capability of Particle Swarm Optimization Algorithms

被引:0
|
作者
Chou, PenChen [1 ]
Chen, JenLian [1 ]
机构
[1] DaYeh Univ, Dept Elect Engn, Changhua 41000, Chunghwa County, Taiwan
来源
ADVANCES IN SWARM INTELLIGENCE, PT I | 2011年 / 6728卷
关键词
Optimization; Optimization Benchmark; Particle Swarm Optimization; Genetic Algorithm; Mutation;
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
Particle Swarm Optimization (PSO), proposed by Professor Kennedy and Eberhart in 1995, attracts many attentions to solve for a lot of optimization problems nowadays. Due to its simplicity of setting-parameters and computational efficiency, it becomes one of the most popular algorithms in optimizations. However, the discrepancy of PSO is the low dimensionality of the problem can be solved. Once the optimized function becomes complicated, the efficiency gained in PSO degradates rapidly. More complex algorithms on PSO required. Therefore, different algorithms will be applied to different problems with difficulties. Three different algorithms are suggested to solve different problems accordinately. In summary, proposed PSO algorithms apply well to problems with different difficulties in the final simulations.
引用
收藏
页码:28 / 37
页数:10
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