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Open AccessJournal ArticleDOI

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

TLDR
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.
About
This article is published in Electronic Notes in Discrete Mathematics.The article was published on 2017-04-01 and is currently open access. It has received 11 citations till now. The article focuses on the topics: Variable neighborhood search & Metaheuristic.

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Citations
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Journal ArticleDOI

Meta-heuristics for reverse logistics: A literature review and perspectives

TL;DR: The previously published papers on reverse logistics are reviewed and classified on the basis of the meta-heuristic approaches adopted and the problem context of the reverse supply chain to discuss the power and flexibility of these methods for solving a set of RL problems.
Journal ArticleDOI

A survey on techniques for cooperative CPU-GPU computing

TL;DR: This survey paper review the various techniques available for CPU-GPU cooperative computing to improve the resource utilization and reduce the energy consumption of heterogeneous systems by cooperatively performing the computation on both multicore CPUs and GPUs.
Journal ArticleDOI

Hybrid CPU-GPU Community Detection in Weighted Networks

TL;DR: This work shares the computational load between the two units: the CPU takes specific samples of the network communities and organizes them in the form of threaded binary trees, and the GPU takes over the heavy load of reading this data and transforming it into a path-matrix.
Journal ArticleDOI

Cooperative versus non-cooperative parallel variable neighborhood search strategies: a case study on the capacitated vehicle routing problem

TL;DR: This work conducts an experimental study for the CVRP using well-known benchmark instances, and presents and investigates three parallelization strategies that coordinate the communication of the multiple processors.
Book ChapterDOI

Basic VNS Algorithms for Solving the Pollution Location Inventory Routing Problem

TL;DR: It is shown that, CPLEX could not compute any feasible solution on another set of ten randomly generated medium-sized instances, with a time limit of five hours, and two Basic Variable Neighborhood Search (BVNS) metaheuristic approaches are proposed.
References
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Journal ArticleDOI

Variable neighborhood search: basics and variants

TL;DR: In this article, the authors present some of VNS basic schemes as well as several VNS variants deduced from these basic schemes, including parallel implementations and hybrids with other metaheuristics.
Journal ArticleDOI

Parallel variable neighbourhood search strategies for the cutwidth minimization problem

TL;DR: Experimental results show that the parallel implementation of the VFS outperforms previous methods in the state of the art for the CMP, and this fact is also confirmed by non-parametric statistical tests.
Journal ArticleDOI

An integrated CPU–GPU heuristic inspired on variable neighbourhood search for the single vehicle routing problem with deliveries and selective pickups

TL;DR: In this article, an algorithm called four-neighbourhood variable neighbourhood search (FN-VNS) was proposed to solve the single vehicle routing problem with deliveries and selective pickups, which consists in finding a route that starts from the depot and visits all delivery customers.
Journal ArticleDOI

Variable neighborhood descent heuristic for solving reverse logistics multi-item dynamic lot-sizing problems

TL;DR: This paper proposes an efficient variable neighborhood descent heuristic algorithm for solving the multi-product dynamic lot sizing problem with product returns and recovery and demonstrates that this approach outperforms the state-of-the-art Gurobi optimizer.
Journal ArticleDOI

General variable neighborhood search for the multi-product dynamic lot sizing problem in closed-loop supply chain

TL;DR: A General Variable Neighborhood Search (GVNS) metaheuristic algorithm for solving the multi-product dynamic lot sizing problem with product returns and recovery, for the first time that such an approach is used for this problem in the literature.
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