Combining TOPSIS and Particle Swarm Optimization for a Class of Nonlinear Bilevel Programming Problems

被引：1
|
作者：
Jia, Liping [1 ]
Zou, Guocheng [1 ]
Fan, Lei [2 ]
机构：
[1] Leshan Normal Univ, Coll Math & Informat Sci, Leshan 614000, Peoples R China
[2] Xidian Univ, Sch Software, Inst Software Engn, Xian 710071, Peoples R China
来源：
2014 TENTH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND SECURITY (CIS) | 2014年
关键词：
nonlinear bilevel programming; PSO; TOPSIS; KKT condition; ALGORITHM;
D O I：
10.1109/CIS.2014.52
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Bilevel programming has a nested structure and widely used in many real-life problems. This paper addresses a kind of nonlinear bilevel programming, the lower level problem is transformed into a series of constraints for the upper level problem by KKT condition. In the transformed problem, the constraints are taken as an objective for the upper level, thus the nonlinear bilevel programming becomes an equivalent two-objective unconstrained optimization problem. To solve the equivalent problem, TOPSISP and particle swarm optimization are combined and then TOPSISPSO is proposed, computational results for two benchmarks are presented to show the effectiveness of the algorithm.
引用
收藏
页码：321 / 325
页数：5
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