GPU-based Approaches for Multiobjective Local Search Algorithms. A Case Study: the Flowshop Scheduling Problem - Archive ouverte HAL Access content directly
Conference Papers Year : 2011

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

(1) , (1) , (1)
1

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.
Fichier principal
Vignette du fichier
EvoCopLuong.pdf (156.21 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

inria-00638811 , version 1 (07-11-2011)

Identifiers

  • HAL Id : inria-00638811 , version 1

Cite

Thé Van Luong, Nouredine Melab, El-Ghazali Talbi. GPU-based Approaches for Multiobjective Local Search Algorithms. A Case Study: the Flowshop Scheduling Problem. 11th European Conference on Evolutionary Computation in Combinatorial Optimisation, 2011, Torino, Italy. ⟨inria-00638811⟩
100 View
202 Download

Share

Gmail Facebook Twitter LinkedIn More