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Solving Method for a Class of Bilevel Linear Programming based on Genetic Algorithms

Guang-Min Wang (wgm97***at***163.com)
Zhong-Ping Wan (zpwan***at***public.wh.hb.cn)
Xian-Jia Wang (xjwang***at***s1000e.wuhee.edu.cn )

Abstract: The paper studies and designs an genetic algorithm (GA) of the bilevel linear programming problem (BLPP) by constructing the fitness function of the upper-level programming problem based on the definition of the feasible degree. This GA avoids the use of penalty function to deal with the constraints, by changing the randomly generated initial population into an initial population satisfying the constraints in order to improve the ability of the GA to deal with the constraints. Finally, the numerical results of some examples indicate the feasibility and effectiveness of the proposed method.

Keywords: bilevel linear programming,genetic algorithm, fitness function

Category 1: Other Topics (Multi-Criteria Optimization )

Category 2: Linear, Cone and Semidefinite Programming (Other )

Category 3: Nonlinear Optimization (Other )

Citation: Wuhan University Report(2003)

Download: [Postscript][PDF]

Entry Submitted: 03/02/2003
Entry Accepted: 03/03/2003
Entry Last Modified: 06/16/2003

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