An Intelligent Particle Swarm Optimization Algorithm Based on Fitness Analysis

doi:10.3969/j.issn.1006-2475.2015.05.005

Abstract

Abstract: When solving multi-dimensional multi-peaks function problems, the standard particle swarm optimization algorithm is not good at local search with high accuracy and its global search ability is also weak, besides, its convergence rate is slow. Therefore, an intelligent particle swarm optimization algorithm based on fitness analysis is presented, into which the “local fitness parameter”, the “global fitness parameter” and the “coordinate rotation method” are introduced. Three multi-dimensional multi-peaks functions are tested to show that this algorithm not only has the ability of local and global search, but also demonstrates faster convergence rate.

Key words: particle swarm optimization, fitness parameters, coordinate rotation

CLC Number:

TP182

LI Cong1, SONG Wen-long2. An Intelligent Particle Swarm Optimization Algorithm Based on Fitness Analysis[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2015.05.005.

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