Journal of Control Science and Engineering (Jan 2017)

Self-Adaptive Artificial Bee Colony for Function Optimization

  • Mingzhu Tang,
  • Wen Long,
  • Huawei Wu,
  • Kang Zhang,
  • Yuri A. W. Shardt

DOI
https://doi.org/10.1155/2017/4851493
Journal volume & issue
Vol. 2017

Abstract

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Artificial bee colony (ABC) is a novel population-based optimization method, having the advantage of less control parameters, being easy to implement, and having strong global optimization ability. However, ABC algorithm has some shortcomings concerning its position-updated equation, which is skilled in global search and bad at local search. In order to coordinate the ability of global and local search, we first propose a self-adaptive ABC algorithm (denoted as SABC) in which an improved position-updated equation is used to guide the search of new candidate individuals. In addition, good-point-set approach is introduced to produce the initial population and scout bees. The proposed SABC is tested on 12 well-known problems. The simulation results demonstrate that the proposed SABC algorithm has better search ability with other several ABC variants.