Adaptive Step Length Bacterial Foraging Algorithm

摘要：

A novel adaptive step length bacterial foraging algorithm (ASBF) for high-dimensional function optimization is presented in this paper. The proposed algorithm have some main advantages on traditional bacterial foraging algorithm such as adaptive step length and a new tumble method to overcome trapping in local optima. The algorithm has been evaluated on standard high-dimensional benchmark functions and compared with improved PSO and Genetic algorithms respectively. The simulation results have demonstrated fast convergence ability and improved optimization accuracy of ASBF.

作者: Vahid Rashtchi Akbar Bayat Hesan Vahedi

作者单位: Department of Electrical Engineering,Faculty of Engineering,Zanjan University,Zanjan,Iran

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems(2009 IEEE 智能计算与智能系统国际会议)

会议地点: 上海

会议语种:英文

页码: 322-326

在线出版日期: 2009-11-20（万方平台首次上网日期，不代表论文的发表时间）