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Identification of strategy parameters for particle swarm optimizer through Taguchi method
Abstract：Particle swarm optimization (PSO), like other evolutionary algorithms is a population-based stochastic algorithm inspired from the metaphor of social interaction in birds, insects, wasps, etc. It has been used for finding promising solutions in complex search space through the interaction of particles in a swarm. It is a well recognized fact that the performance of evolutionary algorithms to a great extent depends on the choice of appropriate strategy/operating parameters like population size,crossover rate, mutation rate, crossover operator, etc. Generally, these parameters are selected through hit and trial process, which is very unsystematic and requires rigorous experimentation. This paper proposes a systematic based on Taguchi method reasoning scheme for rapidly identifying the strategy parameters for the PSO algorithm. The Taguchi method is a robust design approach using fractional factorial design to study a large number of parameters with small number of experiments. Computer simulations have been performed on two benchmark functions-Rosenbrock function and Griewank function-to validate the approach. 作者： Author： KHOSLA Arun[1] KUMAR Shakti[2] AGGARWAL K.K.[3] 作者单位： Department of Electronics and Communication Engineering, National Institute of Technology, Jalandhar 144011, IndiaCentre for Advanced Technology, Haryana Engineering College, Jagadhari 135003, IndiaVice Chancellor, GGS Indraprastha University, Delhi 110006, India 期 刊： 浙江大学学报A(英文版) ISTICEISCI Journal： JOURNAL OF ZHEJIANG UNIVERSITY SCIENCE A 年，卷(期)： 2006, 7(12) 分类号： N941 TP301.6 Keywords： Strategy parameters Particle swarm optimization (PSO) Taguchi method ANOVA 机标分类号： TS9 TN3 机标关键词： Taguchi method evolutionary algorithms fractional factorial design robust design search space 基金项目： Identification of strategy parameters for particle swarm optimizer through Taguchi method[期刊论文] 浙江大学学报A(英文版) --2006, 7(12)Particle swarm optimization (PSO), like other evolutionary algorithms is a population-based stochastic algorithm inspired from the metaphor of social interaction in birds, insects, wasps, etc. It has b...【Identification of strategy parameter】相关文章：
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