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Une approche par relaxation lagrangienne pour l'optimisation d'un réseau de distribution : modèles stochastiques et fiables

Abstract : This thesis deals with the development of models and heuristic algorithms for stochastic distribution network design problems. In the first part, the core decision problem lies in optimally designing a distribution network by finding the optimal distribution centers (DCs) location and the best supplier that would replenish the DCs. The first objective of this project is to join strategics decisions (location of DCs and supplier selection) and operational decision (inventory) in the same optimization model. The goal is to minimize the total fixed location cost, transportation cost, working-inventory cost. The problem is difficult to solve since it integrates all these decisions at the same time with non linear cost function to optimize. We provide an efficient technique which reduces system complexity. The second part of this thesis deals with the design of a distribution network where decisions must be made in the presence of uncertainty. Once the facilities have been constructed in the network, one or more of them may from time to time become unavailable because of some risks. To cope with this uncertain environment, we develop strategic decisions that take into account possible scenarios and strategies need to react when risk events occur. A two-period stochastic programming model is proposed. The goal is to minimize the total first stage cost plus the expected value of the random second stage cost taken trough all scenarios. As solution technique, we propose a Monte Carlo optimization approach combining the sample average approximation scheme and an efficient heuristic based on Lagrangian relaxation to generate efficient solutions and determine tight lower bounds
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Guy Aimé Tanonkou. Une approche par relaxation lagrangienne pour l'optimisation d'un réseau de distribution : modèles stochastiques et fiables. Automatique / Robotique. Université Paul Verlaine - Metz, 2007. Français. ⟨NNT : 2007METZ008S⟩. ⟨tel-01775501⟩



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