AN ADAPTIVE PARAMETER CONTROL STRATEGY FOR ACO

摘要：

Ant Colony Optimization (ACO) has been proved to be one of the best performing algorithms for NP-hard problems as TSP. Many strategies for ACO have been studied, but fewer tuning methodologies have been done on ACOs parameters which influence the algorithm directly. The setting of ACOs parameters is considered as a combinational optimization problem in this paper. The Particle Swarm Optimization (PSO)is introduced to solve this problem, and an adaptive parameter setting strategy is proposed. Its proved to be effective by the experiment based on TSPLIB test.

关键词： Ant Colony Optimization Particle Swarm Optimization Adaptive parameters TSP

作者: ZHI-FENG HAO RUI-CHU CAI HAN HUANG

作者单位: College of Computer Science and Engineering, South China University of Technology, Guangzhou P.R.Chi College of Mathematical Science, South China University of Technology, Guangzhou P.R.China

会议类型: 国际会议

会议名称: 2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

会议地点: 大连

会议语种:英文

页码: 203-206

在线出版日期: 2006-08-13（万方平台首次上网日期，不代表论文的发表时间）