101documents trouvés
High Performance Peer-to-Peer Distributed Computing with Application to Obstacle Problem
T.T.NGUYEN, D.EL BAZ, P.SPITERI, G.JOURJON, M.CHAU
CDA, IRIT-UPS, NICTA
Manifestation avec acte : 24th IEEE International Parallel and Distributed Processing Symposium (IPDPS 2010), Atlanta (USA), 19-23 Avril 2010, 8p. , N° 09748
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121144Solution of multidimensional knapsack problems via cooperation of dynamic programming and branch and bound
V.BOYER, D.EL BAZ, M.ELKIHEL
CDA
Revue Scientifique : European Journal of Industrial Engineering, Vol.4, N°4, pp.434-449, Avril 2010 , N° 10967
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127287Parallélisation de méthode d'optimisation entière sur GPU
D.EL BAZ, L. DUMAS, V.BOYER, M.ELKIHEL, J.M.ENJALBERT
CDA
Manifestation sans acte : ROADEF 2010, Toulouse (France), 24-26 Février 2010, 2p. , N° 09673
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121021Une heuristique pour le problème du sac à dos multiple en varaibles 0-1
M.LALAMI, D.EL BAZ, M.ELKIHEL, V.BOYER
CDA
Manifestation sans acte : ROADEF 2010, Toulouse (France), 24-26 Février 2010, 2p. , N° 09674
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121019A self-adaptive communication protocol with application to high performance peer to peer distributed computing
D.EL BAZ, T.T.NGUYEN
CDA
Manifestation avec acte : 18th Euromicro Conference on Parallel Distributed and Network-Based Processing (PDP 2010), Pise (Italie), 17-19 Février 2010, pp.327-333 , N° 09513
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Mots-Clés / Keywords
Communication Protocols; Self-adaptive protocol; Micro-protocols; High performance computing; Peer to peer computing; Nonlinear optimization; Network flow problems;
Programmation dynamique dense sur GPU
V.BOYER, D.EL BAZ, M.ELKIHEL
CDA
Manifestation sans acte : ROADEF 2010, Toulouse (France), Février 2010, 2p. , N° 09740
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121020Heuristics for the 0-1 multidimensional knapsack problem
V.BOYER, M.ELKIHEL, D.EL BAZ
CDA
Revue Scientifique : European Journal of Operational Research, Vol.199, N°3, pp.658-664, Décembre 2009 , N° 06539
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Abstract
Two heuristics for the 01 multidimensional knapsack problem (MKP) are presented. The first one uses surrogate relaxation, and the relaxed problem is solved via a modified dynamic-programming algorithm. The heuristics provides a feasible solution for (MKP). The second one combines a limited-branch-and-cut-procedure with the previous approach, and tries to improve the bound obtained by exploring some nodes that have been rejected by the modified dynamic-programming algorithm. Computational experiences show that our approaches give better results than the existing heuristics, and thus permit one to obtain a smaller gap between the solution provided and an optimal solution.
Mots-Clés / Keywords
Multidimensional knapsack problem; Dynamic programming; branch and cut; Surrogate relaxation; Heuristics;
Distributed discrete state acquisition and concurent pattern recognition in a MEMS-based smart surface
D.EL BAZ
CDA
Rapport de Contrat : Contrat ANR RoBo 06 Smart Surface n° ANR-06-RoBo-0009, Novembre 2009 , N° 09602
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119240Un protocole de communication auto-adaptatif pour le calcul intensif pair à pair
T.T.NGUYEN, D.EL BAZ
CDA
Manifestation avec acte : Rencontres francophones du Parallélisme, Symposium en Architecture de machines, Conférence Française sur les Systèmes d'Exploitation, RenPar'19/SympA'13/CFSE'7, Toulouse (France), 9-11 Septembre 2009 , N° 09540
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118976A dynamic programming method with dominance technique for the knapsack sharing problem
V.BOYER, D.EL BAZ, M.ELKIHEL
CDA
Manifestation avec acte : 39th International Conference on Computers & Industrial Engineering (CIE39), Troyes (France), 6-8 Juillet 2009, pp.348-353 , N° 09017
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Abstract
In this paper, we propose an original method to solve exactly the knapsack sharing problem (KSP) by using a dynamic programming with dominance technique. The original problem (KSP) is decomposed in a set of knapsack problems. Our method is tested on uncorrelated and correlated instances from the literature. Computational experiences show that our method is able to find an optimal solution of large instances within reasonable computing time.
Mots-Clés / Keywords
Max-min programming; Knapsack sharing problem; Dynamic programming; Combinatorial optimization;