An Approach for Solving Multi-objective Bi- Level Linear Programming Based on Genetic Algorithm

1 th 4 Abstract: This paper studies and designs a genetic algorithm (GA) of the multi-objective bi-level linear programming problems (M OBLPP) by constructing the fitness function of the upper -level programming problems 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. A comparative study of the proposed method and previous methods through numerical results of an example to show the proposed method in this paper is feasible and efficient to solve (MOBLPP). Finally, parametric study of the GA is introduced.

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