会议专题

Parallel Strength Pareto Multi-objective Evolutionary Algorithm

A parallel Strength Pareto Multi-objective Evolutionary Algorithm (PSPMEA) is proposed. PSPMEA is a parallel computing model designed for solving Pareto-based multi-objective optimization problems by using an evolutionary procedure. In this procedure, both global parallelization and island parallel evolutionary algorithm models are used. Each subpopulation evolves separately with different crossover and mutation probability,but they exchange individuals in the elitist archive. The benchmark problems numerical experiment results demonstrate that the proposed method can rapidly converge to the Pareto optimal front and spread widely along the front.

parallel genetic algorithm evolutionary computation multi-objective optimization

Shengwu Xiong Feng Li

School of Computer Science and Technology,Wuhan University of Technology,Wuhan 430070,P.R.China

国际会议

Proceedings of The Fourth International Conference on Parallel and Distribyted Computing,Applications and Technologies(第四届并行与分布式计算应用与技术国际会议)

成都

英文

681-683

2003-08-27(万方平台首次上网日期,不代表论文的发表时间)