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

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dc.contributor.authorWafa Bouguern
dc.date.accessioned2026-06-01T08:52:46Z
dc.date.issued2026
dc.description.abstractThis 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
dc.identifier.issnMD/46
dc.identifier.urihttps://dspace.univ-bba.dz/handle/123456789/1461
dc.language.isoen
dc.publisherUniversity of Mohamed El Bachir El Ibrahimi - Bordj Bou Arréridj
dc.subjectBilevel programming
dc.subjectmulticriteria optimization
dc.subjectglobal optimization
dc.subjectα-dense curves
dc.subjectevolutionary algorithms
dc.subjectDC programming
dc.titleEtude d’un problème d’optimisation à deux niveaux multicritères
dc.typeThesis

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