Etude d’un problème d’optimisation à deux niveaux multicritères

Abstract

This thesis focuses on developing new methods for solving bilevel programming problems and multicriteria optimization problems, through algorithms based on Difference of Convex Functions (DC) programming with regularization, as well as a metaheuristic approach combining particle swarm optimization and grey wolf optimization, using dense curves to simplify the formulation. Numerical results demonstrate high effectiveness in terms of accuracy and computational time, and the approach is extended to multicriteria problems