Parallélisation d'heuristiques d'optimisation sur les GPUs

Abstract : This thesis presents contributions to the resolution (on GPUs) of real optimization problems of large sizes. The vehicle routing problems (VRP) and the hub location problems (HLP) are treated. Various approaches implemented on GPU to solve variants of the VRP. A parallel genetic algorithm (GA) on GPU is proposed to solve different variants of the HLP. The proposed GA adapts its encoding, initial solution, genetic operators and its implementation to each of the variants treated. Finally, we used the GA to solve the HLP with uncertainties on the data.The numerical tests show that the proposed approaches effectively exploit the computing power of the GPU and have made it possible to resolve large instances up to 6000 nodes.
Document type :
Complete list of metadatas

Cited literature [162 references]  Display  Hide  Download
Contributor : Abes Star <>
Submitted on : Friday, June 28, 2019 - 1:02:19 AM
Last modification on : Thursday, July 4, 2019 - 9:16:11 AM


Version validated by the jury (STAR)


  • HAL Id : tel-02167633, version 1


Achraf Berrajaa. Parallélisation d'heuristiques d'optimisation sur les GPUs. Autre [q-bio.OT]. Normandie Université; Université Mohammed Premier Oujda (Maroc), 2018. Français. ⟨NNT : 2018NORMLH31⟩. ⟨tel-02167633⟩



Record views


Files downloads