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Generic models and optimization algorithms for sustainable supply chain network design

Abstract : This thesis focuses on the development of mathematical models and optimization algorithms for the design of sustainable supply chains. We propose single-period, multi-commodity, multi-mode, four level models (suppliers, production facilities, warehouses and customers) covering economic and environmental pillars of sustainable development. The decision variables are related to the location of the intermediate logistics sites (production units and warehouses), the choice of technology and mode of transport, and the determination of product flow. A first model is based solely on minimizing total costs. This model is extended to bi-objective minimization by considering CO2 emissions. We propose an optimization procedure based on the Large Neighborhood Search (LNS) metaheuristic, which had almost never been applied to problems with mixed variables such as design supply chain. Our extension to the bi-objective case involves the use of the multi-directional local search (MDLS). Extensive numerical experiments assess the relevance of our model and compare the performance of our algorithms to those of a state-of-the-art solver.
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Majid Eskandarpour. Generic models and optimization algorithms for sustainable supply chain network design. Automatic Control Engineering. Ecole des Mines de Nantes, 2014. English. ⟨NNT : 2014EMNA0195⟩. ⟨tel-01127634⟩

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