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Parallel and Distributed Hybrid Optimization Models for Grids

Malika Mehdi 1 Charr Jean-Claude 1 Nouredine Melab 1 El-Ghazali Talbi 1 Bouvry Pascal 
1 DOLPHIN - Parallel Cooperative Multi-criteria Optimization
LIFL - Laboratoire d'Informatique Fondamentale de Lille, Inria Lille - Nord Europe
Abstract : This paper deals with hybrid optimization schemes that combine meta-heuristics and exact optimization methods. In particular, Genetic Algorithms (GAs) and the Branch-and-Bound algorithm (B&B). Three parallel hybridization schemes combining GAs and the B&B algorithm are proposed: a parallel relay model where the two algorithms are executed in a pipeline mode, a low level hybrid scheme where a given operator of the GA is replaced by a B&B solver, and a cooperative hybrid scheme where the two algorithms cooperate and exchange information about: best-found solution, promising regions to exploit by the B&B and unexplored regions to explore by the GA.
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Contributor : Malika Mehdi Connect in order to contact the contributor
Submitted on : Thursday, October 7, 2010 - 11:34:28 AM
Last modification on : Thursday, January 20, 2022 - 5:27:50 PM


  • HAL Id : inria-00524202, version 1


Malika Mehdi, Charr Jean-Claude, Nouredine Melab, El-Ghazali Talbi, Bouvry Pascal. Parallel and Distributed Hybrid Optimization Models for Grids. International Conference on Metaheuristics and Nature Inspired Computing (META), Oct 2010, Djerba, Tunisia. ⟨inria-00524202⟩



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