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ISICA
2007
Springer

Fast Multi-swarm Optimization with Cauchy Mutation and Crossover Operation

11 years 11 months ago
Fast Multi-swarm Optimization with Cauchy Mutation and Crossover Operation
The standard Particle Swarm Optimization (PSO) algorithm is a novel evolutionary algorithm in which each particle studies its own previous best solution and the group’s previous best to optimize problems. One problem exists in PSO is its tendency of trapping into local optima. In this paper, a multiple swarms technique(FMSO) based on fast particle swarm optimization(FPSO) algorithm is proposed by bringing crossover operation. FPSO is a global search algorithm witch can prevent PSO from trapping into local optima by introducing Cauchy mutation. Though it can get high optimizing precision, the convergence rate is not satisfied, FMSO not only can find satisfied solutions ,but also speeds up the search. By proposing a new information exchanging and sharing mechanism among swarms. By comparing the results on a set of benchmark test functions, FMSO shows a competitive performance with the improved convergence speed and high optimizing precision.
Qing Zhang, Changhe Li, Yong Liu, Lishan Kang
Added 08 Jun 2010
Updated 08 Jun 2010
Type Conference
Year 2007
Where ISICA
Authors Qing Zhang, Changhe Li, Yong Liu, Lishan Kang
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