计算机工程与应用 ›› 2008, Vol. 44 ›› Issue (6): 59-61.

• 学术探讨 • 上一篇    下一篇

一种基于群智能的快速多目标优化算法

邹卫强1,卜质琼1,2   

  1. 1.广东技术师范学院 信息工程系,广州 510665
    2.武汉大学 国际软件学院,武汉 430072
  • 收稿日期:2007-10-09 修回日期:2007-12-24 出版日期:2008-02-21 发布日期:2008-02-21
  • 通讯作者: 邹卫强

Fast multi-objective optimization algorithm based on swarm intelligence

ZOU Wei-qiang1,BU Zhi-qiong1,2   

  1. 1.Dept. of Information Engineering,Guangdong Polytechnic Normal University,Guangzhou 510665,China
    2.International School of Software,Wuhan University,Wuhan 430072,China
  • Received:2007-10-09 Revised:2007-12-24 Online:2008-02-21 Published:2008-02-21
  • Contact: ZOU Wei-qiang

摘要: 粒子群优化算法是一种典型的仿真群智能的算法。探讨了利用粒子群算法求解多目标优化问题,为了提高算法速度,采用了几何Pareto选择算法作为文档算法,用多方向搜索的办法寻找极端点。实验表明:该算法得到的解的数量多,速度快并且近似前沿的程度比较高。

Abstract: Particle swarm optimization is recognized as a classic algorithm simulating swarm intelligence.A new algorithm based on particle swarm optimization is discussed,which uses geometrical Pareto selection algorithm as archiving algorithm for improving the speed and uses multiple-direction search for seeking extreme points.The experimental results show that this algorithm can obtain many enough solutions and is insensitive to steep fronts,fast and more approximated to the true Pareto front.