Computer Engineering and Applications ›› 2011, Vol. 47 ›› Issue (15): 49-52.

• 研究、探讨 • Previous Articles     Next Articles

Using hybrid particle swarm algorithm for solving constrained multi-objective optimization problem

PEI Shengyu,ZHOU Yongquan   

  1. College of Mathematics and Computer Science,Guangxi University for Nationalities,Nanning 530006,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2011-05-21 Published:2011-05-21

用于约束多目标优化问题的混合粒子群算法

裴胜玉,周永权   

  1. 广西民族大学 数学与计算机科学学院,南宁 530006

Abstract: A hybrid particle swarm algorithm for solving constrained multi-objective optimization problem is proposed,in which two populations are adopted,and Pareto non-dominated ranking,tournament selection,crowding distance method are integrated into a new based wash out rule by improving the update strategy of particles.Finally,four classical functions are used to test the performance of the algorithm.Experimental results show that the proposed approach is an efficient and outperform conventional algorithm.

Key words: particle swarm optimization, constrained optimization, multi-objective optimization, Pareto non-dominated, immune algorithm

摘要: 针对约束多目标优化问题,结合Pareto支配思想、锦标赛选择和排挤距离技术,采用双种群搜索策略,引进免疫机制,对传统的粒子更新策略进行改进,提出一种用于求解约束多目标优化问题的混合粒子群算法。通过4个标准约束多目标函数进行测试,测试结果表明,该方法有效可行,相比传统多目标优化算法更优。

关键词: 粒子群, 约束优化, 多目标优化, Pareto支配, 免疫机制