GPU-based Approaches for Multiobjective Local Search Algorithms. A Case Study: the Flowshop Scheduling Problem

Thé Van Luong 1 Nouredine Melab 1 El-Ghazali Talbi 1
1 DOLPHIN - Parallel Cooperative Multi-criteria Optimization
LIFL - Laboratoire d'Informatique Fondamentale de Lille, Inria Lille - Nord Europe
Abstract : Multiobjective local search algorithms are efficient methods to solve complex problems in science and industry. Even if these heuristics allow to significantly reduce the computational time of the solution search space exploration, this latter cost remains exorbitant when very large problem instances are to be solved. As a result, the use of GPU computing has been recently revealed as an efficient way to accelerate the search process. This paper presents a new methodology to design and implement efficiently GPU-based multiobjective local search algorithms. The experimental results show that the approach is promising especially for large problem instances.
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Communication dans un congrès
Peter Merz and Jin-Kao Hao. 11th European Conference on Evolutionary Computation in Combinatorial Optimisation, 2011, Torino, Italy. Springer, 6622, 2011, Lecture Notes in Computer Science
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Thé Van Luong, Nouredine Melab, El-Ghazali Talbi. GPU-based Approaches for Multiobjective Local Search Algorithms. A Case Study: the Flowshop Scheduling Problem. Peter Merz and Jin-Kao Hao. 11th European Conference on Evolutionary Computation in Combinatorial Optimisation, 2011, Torino, Italy. Springer, 6622, 2011, Lecture Notes in Computer Science. 〈inria-00638811〉

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