多目标粒子群优化算法研究  

Study on multi-objective particle swarm optimization algorithm

作　　者：郑友莲[1] 樊俊青[2] 

机构地区：[1]湖北大学数学与计算机科学学院,湖北武汉430062 [2]中国地质大学计算机学院,湖北武汉430074

出　　处：《湖北大学学报（自然科学版）》2008年第4期351-355,共5页Journal of Hubei University：Natural Science

基　　金：湖北省自然科学基金项目(207ABA044)资助

摘　　要：在过去的十多年,粒子群算法对多目标优化问题的应用研究取得了较大的进展.本文首先描述多目标粒子群优化算法(MOPSO)的基本流程,然后从算法设计与应用等方面回顾MOPSO的研究进展,最后对该算法未来的研究进行了分析和展望.Over the past decade or so, particle swarm optimization algorithm made great progress in the applied research of multi-objective optimization. Firstly, the basic flow of multi-objective particle swarm optimization （MOPSO） was described, and then the progress of MOPSO algorithm in areas such as algorithm design and application was reviewed, lastly, this analysis and outlook about future research of this algorithm were carried out.

关 键 词：多目标优化 粒子群优化 算法设计 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]