计算机工程与应用 ›› 2008, Vol. 44 ›› Issue (11): 43-46.

• 理论研究 • 上一篇    下一篇

求解非线性规划问题的混合粒子群算法

廖 锋,高兴宝   

  1. 陕西师范大学 数学与信息科学学院,西安 710062
  • 收稿日期:2007-10-09 修回日期:2007-12-25 出版日期:2008-04-11 发布日期:2008-04-11
  • 通讯作者: 廖 锋

Hybrid particle swarm optimization to solve nonlinear programming problems

LIAO Feng,GAO Xing-bao   

  1. College of Mathematics and Information Science,Shannxi Normal University,Xi’an 710062,China
  • Received:2007-10-09 Revised:2007-12-25 Online:2008-04-11 Published:2008-04-11
  • Contact: LIAO Feng

摘要: 用粒子群算法求解非线性规划问题时不可避免的会产生不可行点,处理好不可行点是粒子群算法取得良好优化结果的关键。依据粒子的目标函数值与违反约束的程度提出了一种处理不可行点的合理选择方案,并运用融合差分演化的混合粒子群算法求解约束优化问题,数值实验表明该算法的有效性。

关键词: 粒子群, 差分演化, 早熟

Abstract: It’s inevitable to produce infeasible points when the author use particle swarm optimization to solve nonlinear programming problems,and it is very important to handle infeasible points for particle swarm opimization to get good optimization result.The authors propose an reasonable select method to deal with infeasible points based on object function value and violate degree,and apply an hybrid particle swarm optimization algorithm combined differential evolution to solve constrined optimization problems,the numerical experiment indicated that the algorithm is efficient.

Key words: particle swarm, differential evolution, premature