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

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

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.

Angelo Sifaleras | Nikolaos Antoniadis

[1] Angelo Sifaleras,et al. General variable neighborhood search for the multi-product dynamic lot sizing problem in closed-loop supply chain , 2015, Electron. Notes Discret. Math..

[2] Juan José Pantrigo,et al. Parallel variable neighbourhood search strategies for the cutwidth minimization problem , 2016 .

[3] Pierre Hansen,et al. Variable neighborhood search: basics and variants , 2017, EURO J. Comput. Optim..

[4] Angelo Sifaleras,et al. Variable neighborhood descent heuristic for solving reverse logistics multi-item dynamic lot-sizing problems , 2017, Comput. Oper. Res..

[5] Igor Machado Coelho,et al. An integrated CPU–GPU heuristic inspired on variable neighbourhood search for the single vehicle routing problem with deliveries and selective pickups , 2016 .

[6] Teodor Gabriel Crainic,et al. MPI Parallelization of Variable Neighborhood Search , 2012, Electron. Notes Discret. Math..

[7] Marc Sevaux,et al. Solving dynamic memory allocation problems in embedded systems with parallel variable neighborhood search strategies , 2015, Electron. Notes Discret. Math..