1.College of Information Science and Engineering,Guangxi University for Nationalities,Nanning 530006 2.Guangxi Key Laboratory of Hybrid Computation and IC Design Analysis,Guangxi University for Nationalities,Nanning 530006 3.School of Computer and Information Technology,Beijing Jiaotong University,Beijing 100044
Abstract:Pattern search algorithm often falls into local optimization and its efficiency is low. Inspired by swarm intelligence algorithm,a global optimization algorithm,swarm pattern global search algorithm (SPGSA),is proposed. Swarm intelligence is introduced to SPGSA in the evolution process. Thus,SPGSA includes pattern search operator,pattern moving operator,pattern learning operator and pattern dispersion operator.It has a strong ability of global and local search as well as better features of fast convergence and good stability. Comparisons of the simulation results by using standard benchmark functions prove the effectiveness.
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