Differential Evolution for Single-Objective Optimization

摘要：

We perform a comprehensive analysis of Differential Evolution (DE) single-objective (SO) optimization strategies, in comparison to Genetic Algorithms (GAs). A number of benchmark problems are considered. We investigate the algorithms behavior and performance with respect to their parameters setting. We measure the performance in terms of reliability, accuracy and convergence speed.

关键词： Evolutionary Algorithm Differential Evolution Genetic Algorithm Single-Objective optimization

作者: ENRICO ZIO GIORGIO VIADANA

作者单位: Chair at the European Foundation for New Energy, EDF at Ecole Centrale Paris-Supelec, Paris, France Politecnico di Milano, Energy Department, Milano, Italy

会议类型: 国际会议

会议名称: The 7th Inyernational Conference on Mathematical Methods in Reliability:Theory,Methods,Applications(第七届国际可靠性数学、理论、方法与应用会议 MMR2011)

会议地点: 北京

会议语种:英文

页码: 230-237

在线出版日期: 2011-06-20（万方平台首次上网日期，不代表论文的发表时间）