Global Artificial Bee Colony Search Algorithm for Numerical Function Optimization

摘要：

The standard artificial bee colony (ABC) algorithm as a relatively new swarm optimization method is often trapped in local optima in global optimization. In this paper, a novel search strategy of main three procedures of the ABC algorithm is presented. The solutions of the whole swarm are exploited based on the neighbor information by employed bees and onlookers in the ABC algorithm. According to incorporating all employed bees historical best position information of food source into the solution search equation, the improved algorithm that is called global artificial bee colony search algorithm has great advantages of convergence property and solution quality. Some experiments are made on a set of benchmark problems, and the results demonstrate that the proposed algorithm is more effective than other population based optimization algorithms.

关键词： Artificial bee colony Search strategy Particle swarm optimization Function optimization

作者: Guo Peng Cheng Wenming Liang Jian

作者单位: College of Mechanical Engineering, Southwest Jiaotong University Chengdu 610031, China School of Machanical Eengineering & Automation, Xihua University Chengdu 610039, China

会议类型: 国际会议

会议名称: 2011 Seventh International Conference on Natural Computation(第七届自然计算国际会议 ICNC 2011)

会议地点: 上海

会议语种:英文

页码: 1306-1309

在线出版日期: 2011-07-26（万方平台首次上网日期，不代表论文的发表时间）