A Clonal Selection Adaptive Local Search Operator for multi-objective optimization evolutionary algorithm

摘要：

A clonal selection adaptive local search operator for multi-objective optimization evolutionary algorithm is proposed in order to enhance the search capability and expedite convergence speed of the multi-objective evolutionary algorithms. A crossover based adaptive local search algorithm including a method to change the clonal scale of different individuals adaptively according to their position in the whole population is proposed. Test functions with two objectives and three objectives are selected to confirm the performance of the operator. Results show that the clonal selection adaptive local operator makes multi-objective optimization evolutionary algorithm has better performance in convergence and distribution.

关键词： Clonal selection. Adaptive local search operator. Multi-objective optimization evolutionary algorithm.

作者: Yong Li Yu Wang Yuxian Zhang Yuejun An

作者单位: School of Electrical Engineering, Shenyang University of Technology, Shenyang 110870 Department of Automatic Control, Shenyang Aerospace University, Shenyang 110136

会议类型: 国际会议

会议名称: The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

会议地点: 太原

会议语种:英文

页码: 755-757

在线出版日期: 2012-05-23（万方平台首次上网日期，不代表论文的发表时间）