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Applying a Genetic Algorithm to a m-TSP: Case Study of a Decision Support System for Optimizing a Beverage Logistics Vehicles Routing Problem

2021Journal article Open access
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dc.contributor.authorGomes, David E.
dc.contributor.authorIglésias, Maria Inês D.
dc.contributor.authorProença, Ana Beatriz Pena
dc.contributor.authorLima, Tânia M.
dc.contributor.authorGaspar, Pedro Dinis
dc.date.accessioned2022-01-07T15:12:41Z
dc.date.available2022-01-07T15:12:41Z
dc.date.issued2021
dc.description.abstractRoute optimization has become an increasing problem in the transportation and logistics sector within the development of smart cities. This article aims to demonstrate the implementation of a genetic algorithm adapted to a Vehicle Route Problem (VRP) in a company based in the city of Covilhã (Portugal). Basing the entire approach to this problem on the characteristic assumptions of the Multiple Traveling Salesman Problem (m-TSP) approach, an optimization of the daily routes for the workers assigned to distribution, divided into three zones: North, South and Central, was performed. A critical approach to the returned routes based on the adaptation to the geography of the Zones was performed. From a comparison with the data provided by the company, it is predicted by the application of a genetic algorithm to the m-TSP, that there will be a reduction of 618 km per week of the total distance traveled. This result has a huge impact in several forms: clients are visited in time, promoting provider-client relations; reduction of the fixed costs with fuel; promotion of environmental sustainability by the reduction of logistic routes. All these improvements and optimizations can be thought of as contributions to foster smart cities.pt_PT
dc.description.sponsorshipFundação para a Ciência e a Tecnologia (FCT—MCTES) for its financial support via the project UIDB/00151/2020 (C-MAST).pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.3390/electronics10182298pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.6/11583
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.relationCentre for Mechanical and Aerospace Science and Technologies
dc.subjectGenetic algorithmspt_PT
dc.subjectM-TSPpt_PT
dc.subjectVRPpt_PT
dc.subjectDecision support systempt_PT
dc.subjectCase studypt_PT
dc.titleApplying a Genetic Algorithm to a m-TSP: Case Study of a Decision Support System for Optimizing a Beverage Logistics Vehicles Routing Problempt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleCentre for Mechanical and Aerospace Science and Technologies
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00151%2F2020/PT
oaire.citation.issue18pt_PT
oaire.citation.startPage2298pt_PT
oaire.citation.titleElectronicspt_PT
oaire.citation.volume10pt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameLima
person.familyNameGaspar
person.givenNameTânia
person.givenNamePedro Dinis
person.identifier1710267
person.identifier.ciencia-id771E-3B60-A936
person.identifier.ciencia-id6111-9F05-2916
person.identifier.orcid0000-0002-7540-3854
person.identifier.orcid0000-0003-1691-1709
person.identifier.ridV-5052-2017
person.identifier.ridN-3016-2013
person.identifier.scopus-author-id48661120000
person.identifier.scopus-author-id57419570900
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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relation.isAuthorOfPublicationb69e2ba0-43af-4cf7-873e-090fd9fc6c94
relation.isAuthorOfPublication.latestForDiscoveryef58bc1e-8e06-46cc-93e3-bba8e6ed8388
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