A hybrid CPU-GPU parallelization scheme of variable neighborhood search for inventory optimization problems

Nikolaos Antoniadis; Angelo Sifaleras

doi:10.1016/j.endm.2017.03.007

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arXiv · 1704.05132

A hybrid CPU-GPU parallelization scheme of variable neighborhood search for inventory optimization problems

Nikolaos Antoniadis·Angelo Sifaleras

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Abstract

In this paper, we study various parallelization schemes for the Variable Neighborhood Search (VNS) metaheuristic on a CPU-GPU system via OpenMP and OpenACC. A hybrid parallel VNS method is applied to recent benchmark problem instances for the multi-product dynamic lot sizing problem with product returns and recovery, which appears in reverse logistics and is known to be NP-hard. We report our findings regarding these parallelization approaches and present promising computational results.

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Nikolaos Antoniadis, Angelo Sifaleras. 2017-04-17. A hybrid CPU-GPU parallelization scheme of variable neighborhood search for inventory optimization problems. https://doi.org/10.1016/j.endm.2017.03.007

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