期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2013
卷号：48
期号：1
页码：293-302
出版社：Journal of Theoretical and Applied
摘要：The Artificial Bee Colony (ABC) algorithm based on swarm intelligence is a more competitive algorithm than other Evolution Algorithm (EA). The results of recent studies indicate that the ABC algorithm has many advantages but it has two major weaknesses: one is slower convergence speed; the other is getting trapped in local optimal value early. Inspired by differential evolution (DE), different with other improved ABC algorithm based Differential Evolution (DE), we propose a modified ABC algorithm, named it ABC/current-to-best/1, by introducing the best food source (the best solution) and randomly choosing food source (the random solution). Experiments are conducted on a group of 24 benchmark functions. The results testify the performance of ABC/current-to-best/1 algorithm better than original ABC and some pre-existing improved ABC algorithm.
关键词：Artificial Bee Colony; Global Numerical Optimization; Search Strategy; Differential Evolution
