Skip to Main content Skip to Navigation

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.
Document type :
Complete list of metadata

Cited literature [100 references]  Display  Hide  Download
Contributor : Antoine Jeanjean Connect in order to contact the contributor
Submitted on : Tuesday, February 14, 2012 - 4:50:46 PM
Last modification on : Thursday, April 28, 2022 - 3:03:08 PM
Long-term archiving on: : Tuesday, May 15, 2012 - 2:40:16 AM


  • HAL Id : pastel-00670147, version 1



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



Record views


Files downloads