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Modélisation et optimisation de problème de planification de désassemblage dans un environnement incertain

Abstract : Our research proposes to model and optimize the disassembly lot-sizing problem. The contributions presented in this manuscript focus on disassembly planning in certain and uncertain context. We have considered three main models with their resolution approaches: (i) a deterministic multi-period modeling that deals with a multilevel product structure with a commonality of components that aims to maximize total profit. A Mixed Integer Linear Programming (MILP) model is proposed to optimally solve the problem, (ii) a single period stochastic model with a two-level disassembly system and a single type of end-of-life product under random refurbishing lead times. This model seeks to minimize the total expected cost, composed of inventory and backlog costs. A Newboy approach is proposed to solve the problem, and (iii) a multi-period stochastic model which deals with the uncertainty of refurbishing lead times when order crossover is considered. Stochastic Mixed Integer Linear Program, Monte Carlo simulation and scenario aggregation approaches are proposed to solve the proposed model. The performances of the proposed resolution approaches are presented by analyzing the optimization results on a set of randomly generated instances.
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2020IMTA0192_Slama-Ilhem.pdf
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  • HAL Id : tel-03374194, version 1

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Ilhem Slama. Modélisation et optimisation de problème de planification de désassemblage dans un environnement incertain. Recherche opérationnelle [cs.RO]. Ecole nationale supérieure Mines-Télécom Atlantique; Université de Sfax (Tunisie). Faculté des Sciences économiques et de gestion, 2020. Français. ⟨NNT : 2020IMTA0192⟩. ⟨tel-03374194⟩

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