P2P B&B and GA for the Flow-Shop Scheduling Problem

dc.contributor.authorBendjoudi, Ahcène
dc.contributor.authorGuerdah, Samir
dc.contributor.authorMansoura, Madjid
dc.contributor.authorMelab, Nouredine
dc.contributor.authorTalbi, El-Ghazali
dc.date.accessioned2013-06-12T10:15:33Z
dc.date.available2013-06-12T10:15:33Z
dc.date.issued2008-09
dc.description.abstractSolving exactly Combinatorial Optimization Problems (COPs) using a Branch-and-Bound algorithm (B&B) requires a huge amount of computational resources. The efficiency of such algorithm can be improved by its hybridization with meta-heuristics such as Genetic Algorithms (GA) which proved their effectiveness, since they generate acceptable solutions in a reasonable time. Moreover, distributing at large scale the computation, using for instance Peer-to-Peer (P2P) Computing, provides an efficient way to reach high computing performance. In this chapter, we propose ParallelBB and ParallelGA, which are P2P-based parallelization of the B&B and GA algorithms for the computational Grid. The two algorithms have been implemented using the ProActive distributed object Grid middleware. The algorithms have been applied to a mono-criterion permutation flow-shop scheduling problem and promisingly experimented on the Grid5000 computational Grid.fr_FR
dc.identifier.isbn978-3-540-69260-7
dc.identifier.urihttp://dl.cerist.dz/handle/CERIST/201
dc.publisherSpringer-Verlagfr_FR
dc.relation.ispartofMetaheuristics for Scheduling: Distributed Computing Environments, Studies in Computational Intelligence
dc.relation.ispartofseriesMetaheuristics for Scheduling: Distributed Computing Environments, Studies in Computational Intelligencefr_FR
dc.relation.placeBerlin Heidelbergfr_FR
dc.rights.holderSpringer-Verlagfr_FR
dc.structureCalcul Pervasif et Mobilefr_FR
dc.subjectP2P Computing, Branch and Bound, Genetic Algorithms, Grid Middleware, Flow-Shop Scheduling.fr_FR
dc.titleP2P B&B and GA for the Flow-Shop Scheduling Problemfr_FR
dc.typeBook Chapter
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