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Recherche locale pour l'optimisation en variables mixtes : méthodologie et applications industrielles

Abstract : Large mixed-variable optimization problems are often solved by decomposition, with some drawbacks : di culties to guarantee quality or even feasible solutions and technical complexity of development projects. In this thesis, we propose a direct approach, using local search, for solving mixed-variable optimization problems. Our methodology focuses on two points : a large pool of varied moves and an incremental evaluation based on approximate but highly e cient algorithms, working on combinatorial and continuous dimensions simultaneously. First, we present a formwork stocks optimization problem on construction sites. Then, we rely on this methodology to optimize earthworks scheduling for highway and railway projects. Finally, we solve a vehicle routing problem with inventory management. Inventory routing refers to the optimization of transportation costs for the replenishment of customers' inventories : based on consumption forecasts, the vendor organizes delivery routes.
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https://pastel.archives-ouvertes.fr/pastel-00670147
Contributor : Antoine Jeanjean <>
Submitted on : Tuesday, February 14, 2012 - 4:50:46 PM
Last modification on : Wednesday, March 27, 2019 - 4:41:27 PM
Long-term archiving on: : Tuesday, May 15, 2012 - 2:40:16 AM

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Antoine Jeanjean. Recherche locale pour l'optimisation en variables mixtes : méthodologie et applications industrielles. Recherche opérationnelle [cs.RO]. Ecole Polytechnique X, 2011. Français. ⟨pastel-00670147⟩

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