计算机科学 ›› 2013, Vol. 40 ›› Issue (Z11): 115-119.

• 智能控制与优化 • 上一篇    下一篇

基于改进粒子群的双层规划求解算法

赵志刚,王伟倩,黄树运   

  1. 广西大学计算机与电子信息学院 南宁530004;广西大学计算机与电子信息学院 南宁530004;广西大学计算机与电子信息学院 南宁530004
  • 出版日期:2018-11-16 发布日期:2018-11-16
  • 基金资助:
    本文受国家自然科学基金项目(61063031),广西教育厅科研项目(201106LX035)资助

Bi-level Programming Problem Based on Improved Particle Swarm Algorithm

ZHAO Zhi-gang,WANG Wei-qian and HUANG Shu-yun   

  • Online:2018-11-16 Published:2018-11-16

摘要: 提出一种采用粒子群优化算法求解双层规划模型的算法。首先对粒子群优化算法作了改进,然后用改进后的算法求解双层规划模型,通过两个粒子群优化算法之间的协同迭代,同步优化双层规划的上下层,最终求得双层规划模型的最优解。此算法将求解一般双层规划问题转化为通过两个粒子群优化算法的交互迭代来求解上下两层规划问题。通过对几种典型函数的测试,验证了此算法的有效性。

关键词: 粒子群优化算法,双层规划,全局优化,惯性权重,变异算子

Abstract: This paper proposed an algorithm which uses particle swarm optimization (PSO) method to solve the bi-level programming problem (BLPP).A PSO algorithm with adaptive mutation is put forward firstly to improve the performance of standard PSO.Then the modified PSO is used to solve the bi-level programming model.In the proposed algorithm,the interactive iteration between the two PSO optimizes synchronously the two levels of BLPP,and finally obtaining its optimal solution.The experimental results show that the new algorithm can be used to solve the general BLPP.

Key words: Particle swarm optimization algorithm,Bi-level programming problem,Global optimization,Inertia weight,Mutation operator

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