Granular Computing Ranking Method based Multi-objective Genetic Algorithm

摘要：

The key problem is the objective function sorting and fitness assignment in the Multi-Objective Evolutionary Algorithms(MOEAs). This paper regards the data generated in the process of the MOEAs as information system and introduces the method of the Granular Computing(GrC) to disposal the information system. Based on the dominate relationship in the information system, we get the dominance granule of the objective function, and adopt the granularity of dominance granule as the criteria of individual superiority, handle the incomparable characteristic of the Pareto solution set to form a quick sorting algorithm. Based on it, a multi-objective genetic algorithm is proposed. The result of the experiment shows that this method improves the efficiency of the MOEAs significantly and satisfies the requirements of the convergence.

关键词： Multi-objective Optimization Granularity Granular Computing Genetic Algorithm

作者: Yan Gao-wei XIE Gang Chen Ze-hua

作者单位: College of Information Engineering Taiyuan University of Technology Taiyuan, China

会议类型: 国际会议

会议名称: 2011 International Conference on Information and Computer Networks(ICICN 2011)(2011年信息与计算机网络国际会议)

会议地点: 贵阳

会议语种:英文

页码: 369-373

在线出版日期: 2011-01-26（万方平台首次上网日期，不代表论文的发表时间）