DocumentCode :
3281163
Title :
A New Approach for Solving Linear Bilevel Programming Using Differential Evolution
Author :
Kejia Pan ; Yan Yang ; Jianli Liu
Author_Institution :
Key Lab. of Metallogenic Prediction of Nonferrous Metals, Central South Univ., Changsha, China
fYear :
2012
fDate :
25-28 Aug. 2012
Firstpage :
453
Lastpage :
456
Abstract :
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.
Keywords :
evolutionary computation; linear programming; particle swarm optimisation; DE; GA; Kuhn-Tucker conditions; LBP; PSO; differential evolution; linear bilevel programming; lower level programming problem; penalty function; randomly generated initial population; Genetic algorithms; Linear programming; Programming profession; Sociology; Statistics; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Genetic and Evolutionary Computing (ICGEC), 2012 Sixth International Conference on
Conference_Location :
Kitakushu
Print_ISBN :
978-1-4673-2138-9
Type :
conf
DOI :
10.1109/ICGEC.2012.24
Filename :
6456886
Link To Document :
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