计算机工程与应用 ›› 2008, Vol. 44 ›› Issue (33): 66-68.DOI: 10.3778/j.issn.1002-8331.2008.33.021

• 理论研究 • 上一篇    下一篇

分散搜索算法求解多目标优化问题

刘 强,周育人   

  1. 华南理工大学 计算机科学与工程学院,广州 510640
  • 收稿日期:2007-12-18 修回日期:2008-03-17 出版日期:2008-11-21 发布日期:2008-11-21
  • 通讯作者: 刘 强

Scatter search for multi-objective optimization problem

LIU Qiang,ZHOU Yu-ren   

  1. Department of Computer Science and Engineering,South China University of Technology,Guangzhou 510640,China
  • Received:2007-12-18 Revised:2008-03-17 Online:2008-11-21 Published:2008-11-21
  • Contact: LIU Qiang

摘要: 最近涌现了各种进化方法来解决多目标优化问题,分散搜索也是一种可以解决多目标问题的算法。该算法的结构引用进化算法的杂交和变异算子来增强它的性能,但该算法与其他进化算法的不同在于一系列操作策略不再基于随机性原理,而是运用“分散-收敛集聚”的迭代机制。论文在多目标优化问题区域讨论分散搜索算法,寻找多目标的非支配集或Pareto最优解。实验表明,分散搜索算法具有很好的收敛性和分布性。

关键词: 分散搜索算法, 遗传算法, Pareto最优解

Abstract: Scatter search algorithm can solve the multi-objective optimization problem which enhancing it’s performance by using genetic algorithm crossover and mutation operator.Operating strategy of scatter search is not based on the princlple of stochastic.It is based on “distributing-convergence collecting”to inerative mechanism.This paper analyzes the scatter search in multi-objective optimization problem region and finds the Pareto optimal solutions.The experiment results show that this algorithm is effective.

Key words: scatter search algorithm, genetic algorithm, Pareto optimal solution