Abstract
We present a parallel implementation of an heuristic for the multi capacity vehicle routing problem on GPU. This algorithm involves two kinds of decision: the selection of a mix of vehicles among the available vehicle types and the routing of the selected vehicles. The proposed algorithm computes in parallel an initial solution (tours), and then calculates in parallel all the possible cases to obtain the more suitable vehicles to be used. Finally an improved procedure of the cost of all pairs of neighboring tours on GPU, is developed. In order to highlight the performance of our approach, Ochi (in Parallel and distributed processing, 216−224 [11]) and Karagul (in GU J Sci 27(3):979−986 [7]) test problems and random problems are used. Obtained experimental results on GPU outperform other implementations in execution times and quality of solutions. This means that our algorithm is well suited to the computational power of the GPU and our implementation exploits efficiently the power of the GPU.
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We thank Pr. K. Karagul who provided us the instances test.
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Benaini, A., Berrajaa, A., Daoudi, E.M. (2017). Parallel Implementation of the Multi Capacity VRP on GPU. In: Rocha, Á., Serrhini, M., Felgueiras, C. (eds) Europe and MENA Cooperation Advances in Information and Communication Technologies. Advances in Intelligent Systems and Computing, vol 520. Springer, Cham. https://doi.org/10.1007/978-3-319-46568-5_36
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