计算机工程与应用 ›› 2007, Vol. 43 ›› Issue (3): 40-40.

• 学术探讨 • 上一篇    下一篇

求解约束化问题的人工鱼群算法

王锡淮 郑晓鸣 肖健梅   

  1. 上海海运学院
  • 收稿日期:2006-01-25 修回日期:1900-01-01 出版日期:2007-01-21 发布日期:2007-01-21
  • 通讯作者: 肖健梅

Artificial Fish-Swarm Algorithm for Solving Constrained Optimization Problems

JianMei Xiao   

  • Received:2006-01-25 Revised:1900-01-01 Online:2007-01-21 Published:2007-01-21
  • Contact: JianMei Xiao

摘要: 在利用人工鱼群算法求解约束问题时,处理好约束条件是取得好的优化效果的关键。本文引入了半可行域的概念,并结合人工鱼群算法(Artificial Fish-Swarm Algorithm, AFSA)本身的特点,设计了基于竞争选择和惩罚函数的适应度函数,从而得到了一个利用ASFA算法求解约束优化问题的新的进化算法。实验证明了算法的有效性。

关键词: 约束优化问题, 人工鱼群算法, 半可行域, 竞争原则

Abstract: In trying to solve constrained optimization problems by artificial fish-swarm algorithm (AFSA), the way to handle the constrained conditions is the key factor for success. In this paper, we introduced the concept of semi-feasible region. Making use of characteristics of artificial fish-swarm algorithm, we designed the fitness function of evolutionary algorithm, which is based on tournament selection and penalty function. Then a new method is proposed, which means using the AFSA to solve constrained optimization problems. Numerical experiments demonstrate the effect of the method.

Key words: constrained optimization problems, artificial fish-swarm algorithm, semi-feasible region, tournament selection