文献类型：期刊文献

英文题名：Evolutionary algorithm based on the evolution of Pareto archive and individual migration

作者：Qi, Rongbin[1]; Ma, Tianyi[2]; Sun, Fan[1]; Qian, Feng[1]

机构：[1] Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, China; [2] Shanghai Business School, Shanghai, China

年份：2011

起止页码：90

外文期刊名：2011 International Symposium on Advanced Control of Industrial Processes, ADCONIP 2011

收录：EI(收录号：20113014181500)

语种：英文

外文关键词：Multiobjective optimization

摘要：An evolutionary algorithm based on the parallel evolution of multiple single objective populations and Pareto archive population is proposed, which is not only suitable for solving multi-objective optimization, but also effective for multimodal function. For each single objective population, single objective evolutionary algorithm is applied to optimize separately each of multi-objective functions, where individuals generated by tournament selection from the union of single objective and Pareto Archive population form the single objective population of next generation. Especially, individuals in Pareto archive population also join evolutionary operations. Simulations manifest that the proposed method can realize the search from multiple directions to obtain the non-dominated solutions scattered more uniformly over the Pareto frontier with better convergence metric compared to well-known NSGA-II algorithm. Individual migration from Pareto archive population by tournament selection is also proved to have the advantage in improving the converging speed and converging precision. Moreover, for multimodal single objective function, simulations also show that ideal optimizing solution can be obtained by properly separating single objective function into multi-objective function and applying the above method. ? 2011 Zhejiang University.