灰狼优化算法研究综述

doi:10.11896/j.issn.1002-137X.2019.03.004

Abstract

Abstract: Grey wolf optimization (GWO) algorithm is a new kind of swarm-intelligence-based algorithm and some significant developments have been made since its introduction in 2014.GWO has been successfully applied in a variety of fields due to its simplicity and efficiency.This paper provided a complete survey on GWO,including its search mechanism,implementation process,relative merits,improvements and applications.The studies on GWO about its improvements including improvement of population initialization,search mechanism,and parameters were especially discussed.The application status of GWO in aspect of parameter optimization combinatorial optimization and complex function optimization was summarized.Finally,some novel research directions for future development of this powerful algorithm were given.

Key words: Grey wolf optimization algorithm, Parameter optimization, Search mechanism, Swarm intelligence

CLC Number:

TP301

ZHANG Xiao-feng, WANG Xiu-ying. Comprehensive Review of Grey Wolf Optimization Algorithm[J].Computer Science, 2019, 46(3): 30-38.

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