A novel approach for solving bi-level mono-objective and multi-objective programming problems using evolutionary algorithms

Autores

  • Wafa Bouguern Mathematical Analysis and Applications Laboratory, Department of Mathematics, University Mohamed El Bachir El Ibrahimi of Bordj Bou Arreridj, El Anasser 34030, Algeria https://orcid.org/0000-0002-5565-3581
  • Smail Addoune Mathematical Analysis and Applications Laboratory, Department of Mathematics, University Mohamed El Bachir El Ibrahimi of Bordj Bou Arreridj, El Anasser 34030, Algeria
  • Hanene Debbiche Mathematical Analysis and Applications Laboratory, Department of Mathematics, University Mohamed El Bachir El Ibrahimi of Bordj Bou Arreridj, El Anasser 34030, Algeria

DOI:

https://doi.org/10.18540/jcecvl10iss9pp20661

Palavras-chave:

Nonlinear bi-level programming, Multicriteria optimization, optimization

Resumo

Bi-level programming problems (BLP) constitute an important class of non-convex optimization problems, which makes it challenging to find a global optimal solution. In this article, we propose an efficient technique to solve this category of problems. We reformulated the initial problem as a single-level optimization problem using the optimal value function of the lower-level problem. To solve the latter, we employed a technique based on -dense curves to approximate the value function of the lower-level problem. Two evolutionary algorithms were then used to solve the reformulated problem. Furthermore, we extended our method to address multi-objective bi-level programming problems with a single objective at the upper level and multiple objectives at the lower level, known as a semi-vectorial bi-level programming problem. Several numerical experiments on nonlinear BLP show the outstanding efficiency of our approach.

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Publicado

2024-12-17

Como Citar

Bouguern, W., Addoune, S., & Debbiche, H. (2024). A novel approach for solving bi-level mono-objective and multi-objective programming problems using evolutionary algorithms. The Journal of Engineering and Exact Sciences, 10(9), 20661. https://doi.org/10.18540/jcecvl10iss9pp20661

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