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dc.contributor.authorYelmewad P.
dc.contributor.authorTalawar B.
dc.date.accessioned2021-05-05T10:15:51Z-
dc.date.available2021-05-05T10:15:51Z-
dc.date.issued2020
dc.identifier.citationProceedings of CONECCT 2020 - 6th IEEE International Conference on Electronics, Computing and Communication Technologies , Vol. , , p. -en_US
dc.identifier.urihttps://doi.org/10.1109/CONECCT50063.2020.9198667
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/14835-
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.en_US
dc.titleGPU-based Parallel Heuristics for Capacited Vehicle Routing Problemen_US
dc.typeConference Paperen_US
Appears in Collections:2. Conference Papers

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