A Sustainable Multi-Objective Model for Capacitated-Electric-Vehicle-Routing-Problem Considering Hard and Soft Time Windows as Well as Partial Recharging

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dc.authoridKHALILZADEH, MOHAMMAD/0000-0002-2373-8505
dc.authoridAntucheviciene, Jurgita/0000-0002-1734-3216
dc.authoridHeidari, Ali/0000-0001-8714-125X
dc.authorwosidAntucheviciene, Jurgita/W-6112-2018
dc.contributor.authorAzadi, Amir Hossein Sheikh
dc.contributor.authorKhalilzadeh, Mohammad
dc.contributor.authorAntucheviciene, Jurgita
dc.contributor.authorHeidari, Ali
dc.contributor.authorSoon, Amirhossein
dc.date.accessioned2024-05-19T14:39:49Z
dc.date.available2024-05-19T14:39:49Z
dc.date.issued2024
dc.departmentİstinye Üniversitesien_US
dc.description.abstractDue to the high pollution of the transportation sector, nowadays the role of electric vehicles has been noticed more and more by governments, organizations, and environmentally friendly people. On the other hand, the problem of electric vehicle routing (EVRP) has been widely studied in recent years. This paper deals with an extended version of EVRP, in which electric vehicles (EVs) deliver goods to customers. The limited battery capacity of EVs causes their operational domains to be less than those of gasoline vehicles. For this purpose, several charging stations are considered in this study for EVs. In addition, depending on the operational domain, a full charge may not be needed, which reduces the operation time. Therefore, partial recharging is also taken into account in the present research. This problem is formulated as a multi-objective integer linear programming model, whose objective functions include economic, environmental, and social aspects. Then, the preemptive fuzzy goal programming method (PFGP) is exploited as an exact method to solve small-sized problems. Also, two hybrid meta-heuristic algorithms inspired by nature, including MOSA, MOGWO, MOPSO, and NSGAII_TLBO, are utilized to solve large-sized problems. The results obtained from solving the numerous test problems demonstrate that the hybrid meta-heuristic algorithm can provide efficient solutions in terms of quality and non-dominated solutions in all test problems. In addition, the performance of the algorithms was compared in terms of four indexes: time, MID, MOCV, and HV. Moreover, statistical analysis is performed to investigate whether there is a significant difference between the performance of the algorithms. The results indicate that the MOSA algorithm performs better in terms of the time index. On the other hand, the NSGA-II-TLBO algorithm outperforms in terms of the MID, MOCV, and HV indexes.en_US
dc.identifier.doi10.3390/biomimetics9040242
dc.identifier.issn2313-7673
dc.identifier.issue4en_US
dc.identifier.pmid38667253en_US
dc.identifier.scopus2-s2.0-85191605488en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org10.3390/biomimetics9040242
dc.identifier.urihttps://hdl.handle.net/20.500.12713/4854
dc.identifier.volume9en_US
dc.identifier.wosWOS:001210098600001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherMdpien_US
dc.relation.ispartofBiomimeticsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.snmz20240519_kaen_US
dc.subjectCapacitated Evrpen_US
dc.subjectSustainabilityen_US
dc.subjectPartial Rechargingen_US
dc.subjectHard And Soft Time Windowsen_US
dc.subjectEpsilon-Constrainten_US
dc.subjectNature-Inspired Algorithmsen_US
dc.titleA Sustainable Multi-Objective Model for Capacitated-Electric-Vehicle-Routing-Problem Considering Hard and Soft Time Windows as Well as Partial Rechargingen_US
dc.typeArticleen_US

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