一种基于云模型的多目标进化算法.pdfVIP

41 3 Vol.41, No.3 2012 6 Information and Control Jun., 2012 DOI 10.3724/SP.J.1219.2012.00326 1 1 1 1 2 1. 525000 2. 410081 CMOEA X 0/1 CMOEA NSGA-II SPEA2 CMOEA Pareto Pareto Pareto TP273 A 1002-0411(2012)-03-0326-07 A Multi-Objective Evolutionary Algorithm Based on Cloud Model XU Bo1 PENG Zhiping1 CHEN Xiaolong1 KE Wende1 YU Jianping2 (1. Department of Computer Science and Technology, Guangdong University of Petrochemical Technology, Maoming 525000, China; 2. College of Mathematics and Computer Science, Hunan Normal University, Changsha 410081, China) Abstract: A cloud model-based multi-objective evolutionary algorithm (CMOEA) is proposed based on the multi- objective evolutionary algorithm. In CMOEA, a new mutation operator that adaptively adjusts the mutation probability is designed to guarantee the good local searching ability. To maintain the diversity of solutions, the niche technology is exploited, where the niche radius is dynamically adjusted according to the X conditions cloud generator. Meanwhile, the dy- namic calculation of crowding distance for individuals and the estimation of the individual congestion intensity by the cloud model are conducted at the same time, which is then followed by the eliminating process that removes the excess population one by one to keep non-inferior solutions for distribution. Finally, the multi-objective 0/1 knapsack problem is employed to test the performance of CMOEA. Experimental results indicate that compared with the currently most eff