一种求解线性二层多目标规划的粒子群优化方法  

Particle Swarm Optimization Based Approach for Solving A Class of Linear Bilevel Multi-objective Programming Problem

作　　者：胡密[1] 毛和水[1] 卢仕峰 刘伟[1] 吕一兵[1] 

机构地区：[1]长江大学信息与数学学院,湖北荆州434023

出　　处：《长江大学学报（自科版）（上旬）》2013年第10期6-10,4,共6页JOURNAL OF YANGTZE UNIVERSITY (NATURAL SCIENCE EDITION) SCI ＆ ENG

基　　金：国家自然科学基金资助项目(11201039;61273179);湖北省优秀中青年项目(Q20121216);湖北省教育厅重点项目(D20101304);大学生创新训练项目(201210489334)

摘　　要：粒子群算法是一种新兴的优化技术。由于粒子群算法实现简单,可调参数少,已得到广泛研究和应用。根据粒子群算法能够有效获得不可微多目标规划Pareto最优解的特点,设计了线性二层多目标规划的粒子群算法:采用以下层问题的K-T最优性条件代替下层问题的思想,将线性二层多目标规划转化为带互补约束的不可微多目标规划问题,然后对所得到的不可微多目标规划问题设计粒子群算法,从而得到线性二层多目标规划问题的Pareto最优解。数值结果表明所设计的算法是可行、有效的。Particle swarm optimization(PSO)is a new optimization technique.As PSO can be easily implemented and few parameters need to be tuned,it has been successfully applied to many areas.Following the method of replacing the lower level problem with its KT optimality conditions,the linear bilevel multi-objective programming problem is transformed into the corresponding non-differentiable multi-objective programming problem.Then the Pareto optimal solutions of the linear multi-objective programming problem is obtained by solving the non-differentiable multi-objective programming problem using PSO algorithm.The numerical result shows that the PSO algorithm is feasible and efficient.

关 键 词：线性二层多目标规划 K-T条件 粒子群算法 PARETO最优解 

分 类 号：O224[理学—运筹学与控制论]