GPU-based Parallel Heuristics for Capacited Vehicle Routing Problem

Simple item page
dc.contributor.authorYelmewad, P.
dc.contributor.authorTalawar, B.
dc.date.accessioned2026-02-06T06:36:46Z
dc.date.issued2020
dc.description.abstractThis paper presents the novel GPU-based parallel strategy for the heuristic algorithms to solve the large-scale Capacited Vehicle Routing Problem (CVRP). A combination of five improvement heuristic approaches has been used to improve the constructed feasible solution. It is noticed that a large amount of CPU time is spent in the solution improvement phase while improving a feasible solution. We aim to discover an independent part of the improvement heuristic approaches and make it run over the GPU platform simultaneously. The proposed parallel version has been tested on large-scale instances of up to 20000 customers. The parallel version offers speedup up to 176.12 × compared to the corresponding sequential version. © 2020 IEEE.
dc.identifier.citationProceedings of CONECCT 2020 - 6th IEEE International Conference on Electronics, Computing and Communication Technologies, 2020, Vol., , p. -
dc.identifier.urihttps://doi.org/10.1109/CONECCT50063.2020.9198667
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/30664
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.subjectCapacited Vehicle Routing Problem
dc.subjectGPU
dc.subjectHeuristic Algorithm
dc.subjectImprovement Heuristics
dc.subjectParallel Strategy
dc.titleGPU-based Parallel Heuristics for Capacited Vehicle Routing Problem

Files

Collections

Conference Papers