A new approach for solving linear bilevel programming using differential evolution

被引：1
|
作者：
Pan, Kejia [1 ]
Yang, Yan [2 ]
Liu, Jianli [3 ]
机构：
[1] Cent South Univ Technol, Sch Geosci & Infophys, Minist Educ, Key Lab Metallogen Predict Nonferrous Met, Changsha 410083, Hunan, Peoples R China
[2] Southwest Petr Univ Chengdu, Coll Sci, Chengdu, Peoples R China
[3] Shanghai Univ, Dept Math, Shanghai, Peoples R China
来源：
2012 SIXTH INTERNATIONAL CONFERENCE ON GENETIC AND EVOLUTIONARY COMPUTING (ICGEC) | 2012年
关键词：
Linear bilevel programming; differential evolution; genetic algorithm; Kuhn-Tucker conditions; ALGORITHM; OPTIMIZATION;
D O I：
10.1109/ICGEC.2012.24
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper, a differential evolution (DE) algorithm is developed for solving the linear bilevel programming (LBP) problem. By use of Kuhn-Tucker conditions of the lower level programming problem, the LBP is transferred into a single level programming which can be solved by DE algorithm. This DE algorithm avoids the use of penalty function to deal with the constrains, by changing the randomly generated initial population into an initial population satisfying the constraints in order to improve the ability of the DE to deal with the constrains. The performance of the proposed approach is ascertained by comparing the results with GA and PSO using two problems in the literature.
引用
收藏
页码：453 / 456
页数：4
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