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论文类型：期刊论文

发表时间：2012-01-01

发表刊物：Advanced Science Letters

收录刊物：Scopus

卷号：11

期号：1

页面范围：503-506

ISSN号：19366612

摘要：Artificial bee colony (ABC) algorithm as an optimization algorithm based on swarm intelligence has been applied to solve many kinds of numerical function optimization problems and performs well in most cases. Unfortunately, the original and most existing forms of ABCs cannot solve multimodal optimization problems because of the global selection mechanism used in ABC algorithm, which can locate only one global optimum. This paper adjusts ABC algorithm capturing both global and local optima and applies it for multimodal optimization. We test ABC algorithm on a set of standard functions and compare the performance with that of classic lbest Particle Swarm Optimization algorithms r2pso, r3pso using a ring topology as well as their variants r2pso-lhc and r3psolhc. Experiments show that ABC algorithm outperforms PSOs in almost all of the experiments and can solve multimodal function optimization problems very well. ? 2012 American Scientific Publishers. All rights reserved.