Hybrid Gravitational Search and Clonal Selection Algorithm for Global Optimization

摘要：

　　In recent years, there has been a growing interest in algo rithms inspired by the behaviors of natural phenomena.However, the performance of any single pure algorithm is limited by the size and com plexity of the problem.To further improve the search effectiveness and solution robustness, hybridization of different algorithms is a promising research direction.In this paper, we propose a hybrid iteration algorithm by combing the gravitational search algorithm with the clonal selection.The gravitational search performs exploration in the search space, while the clonal selection is implemented to carry out exploitation within the neighborhood of the solutio found by gravitational search.The emerged hybrid algorithm, called GSCSA, thus reasonably combines the charac teristics of both base algorithms.Experimental results based on several benchmark functions demonstrate the superiority of the proposed algo rithm in terms of solution quality and convergence speed.

关键词： gravitational search clonal selection hybridization

作者: Shangce Gao Hongjian Chai Beibei Chen Gang Yang

作者单位: College of Information Science and Technology, Donghua University, China School of Information, Renmin University of China

会议类型: 国际会议

会议名称: 4th international Conference,ICSI2013(第4届群体智能国际会议)

会议地点: 哈尔滨

会议语种:英文

页码: 1-10

在线出版日期: 2013-06-12（万方平台首次上网日期，不代表论文的发表时间）