A Pareto-Based Differential Evolution Algorithm for Multi-objective Optimization Problems

摘要：

A new Pareto-based differential evolution (PDE) algorithm for solving multi-objective optimization problems was proposed by applying the nondominated sorting and ranking selection procedure developed in NSGA-II to select nondominated individuals to constitute a nondominated solution set. The PDE algorithm was validated using eight benchmark cases. The experimental results show that PDE, compared with NSGA-II algorithm, can find many Pareto optimal solutions distributed onto the Pareto front uniformly, which is an effective method to solve multi-objective optimization problems.

关键词： differential evolution Pareto multi-objective optimization NSGA-II

作者: Ruhai Lei Yuhu Cheng

作者单位: School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou, Jiangsu 221116 China

会议类型: 国际会议

会议名称: The 22nd China Control and Decision Conference(2010年中国控制与决策会议)

会议地点: 徐州

会议语种:英文

页码: 1608-1613

在线出版日期: 2010-05-26（万方平台首次上网日期，不代表论文的发表时间）