Title: A New Kind of the Particle Swarm Optimization Algorithm
Abstract: The particle swarm optimization algorithm is a new kind of Optimization algorithm.Improving the efficiency of the algorithm is current’s research trend.In this paper,a new particle swarm optimization algorithm(TSAPSO) is proposed.In order to balance the overall and partial search ability of the algorithm,the algorithm makes the parameter w of PSO altering with target function.The algorithm also assumes that particles are divided into two swarms,which are primary swarm and partial swarm.In every iteration,the change rate of fitness is calculated,if the change rate of fitness is low,the bad particles of primary swarm are replaced by good particles of partial swarm.This al-gorithm improves variety of particles and reduce the probability of bad result.Four kind of functions are tested by this algorithm,results show that the TSAPSO is better than PSO.
Publication Year: 2010
Publication Date: 2010-01-01
Language: en
Type: article
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