文章基本信息

标题：An Artificial Bee Colony Algorithm with Random Location Updating
本地全文：下载
作者：Lijun Sun ; Tianfei Chen ; Qiuwen Zhang 等
期刊名称：Scientific Programming
印刷版ISSN：1058-9244
出版年度：2018
卷号：2018
DOI：10.1155/2018/2767546
出版社：Hindawi Publishing Corporation
摘要：As a novel swarm intelligence algorithm, artificial bee colony (ABC) algorithm inspired by individual division of labor and information exchange during the process of honey collection has advantage of simple structure, less control parameters, and excellent performance characteristics and can be applied to neural network, parameter optimization, and so on. In order to further improve the exploration ability of ABC, an artificial bee colony algorithm with random location updating (RABC) is proposed in this paper, and the modified search equation takes a random location in swarm as a search center, which can expand the search range of new solution. In addition, the chaos is used to initialize the swarm population, and diversity of initial population is improved. Then, the tournament selection strategy is adopted to maintain the population diversity in the evolutionary process. Through the simulation experiment on a suite of unconstrained benchmark functions, the results show that the proposed algorithm not only has stronger exploration ability but also has better effect on convergence speed and optimization precision, and it can keep good robustness and validity with the increase of dimension.