A Clustering Approach for the Optimal Siting of Recharging Stations in the Electric Vehicle Routing Problem with Time Windows

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Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorLos Andes University-
Autor(es): dc.contributorEAFIT University-
Autor(es): dc.creatorSánchez, Danny García-
Autor(es): dc.creatorTabares, Alejandra-
Autor(es): dc.creatorFaria, Lucas Teles-
Autor(es): dc.creatorRivera, Juan Carlos-
Autor(es): dc.creatorFranco, John Fredy-
Data de aceite: dc.date.accessioned2025-08-21T22:01:44Z-
Data de disponibilização: dc.date.available2025-08-21T22:01:44Z-
Data de envio: dc.date.issued2022-04-28-
Data de envio: dc.date.issued2022-04-28-
Data de envio: dc.date.issued2022-04-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.3390/en15072372-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/223747-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/223747-
Descrição: dc.descriptionTransportation has been incorporating electric vehicles (EVs) progressively. EVs do not produce air or noise pollution, and they have high energy efficiency and low maintenance costs. In this context, the development of efficient techniques to overcome the vehicle routing problem becomes crucial with the proliferation of EVs. The vehicle routing problem concerns the freight capacity and battery autonomy limitations in different delivery-service scenarios, and the challenge of best locating recharging stations. This work proposes a mixed-integer linear programming model to solve the electric location routing problem with time windows (E-LRPTW) considering the state of charge, freight and battery capacities, and customer time windows in the decision model. A clustering strategy based on the k-means algorithm is proposed to divide the set of vertices (EVs) into small areas and define potential sites for recharging stations, while reducing the number of binary variables. The proposed model for E-LRPTW was implemented in Python and solved using mathematical modeling language AMPL together with CPLEX. Performed tests on instances with 5 and 10 clients showed a large reduction in the time required to find the solution (by about 60 times in one instance). It is concluded that the strategy of dividing customers by sectors has the potential to be applied and generate solutions for larger geographical areas and numbers of recharging stations, and determine recharging station locations as part of planning decisions in more realistic scenarios.-
Descrição: dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)-
Descrição: dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)-
Descrição: dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)-
Descrição: dc.descriptionDepartment of Electrical Engineering São Paulo State University (UNESP), São Paulo-
Descrição: dc.descriptionDepartment of Industrial Engineering Los Andes University-
Descrição: dc.descriptionDepartment of Energy Engineering São Paulo State University (UNESP), São Paulo-
Descrição: dc.descriptionDepartment of Mathematical Sciences EAFIT University-
Descrição: dc.descriptionDepartment of Electrical Engineering São Paulo State University (UNESP), São Paulo-
Descrição: dc.descriptionDepartment of Energy Engineering São Paulo State University (UNESP), São Paulo-
Descrição: dc.descriptionCAPES: 001-
Descrição: dc.descriptionCNPq: 152002/2016-2-
Descrição: dc.descriptionFAPESP: 2017/02831-8-
Descrição: dc.descriptionCNPq: 313047/2017-0-
Descrição: dc.descriptionCAPES: 88881.134450/2016-01-
Idioma: dc.languageen-
Relação: dc.relationEnergies-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectcharging stations-
Palavras-chave: dc.subjectelectric vehicles-
Palavras-chave: dc.subjectk-means algorithm-
Palavras-chave: dc.subjectlocation routing problem with time windows-
Palavras-chave: dc.subjectmixed-integer linear programming-
Palavras-chave: dc.subjectvehicle routing-
Título: dc.titleA Clustering Approach for the Optimal Siting of Recharging Stations in the Electric Vehicle Routing Problem with Time Windows-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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