Multi-objective mixed bus fleet charging schedule problem with Time-of-Use for real-world data-sets

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dc.contributor.authorJarvis, Padraighen
dc.contributor.authorCliment, Lauraen
dc.contributor.authorArbelaez, Alejandroen
dc.contributor.funderScience Foundation Irelanden
dc.contributor.funderEuropean Regional Development Funden
dc.date.accessioned2025-04-04T11:37:45Z
dc.date.available2025-04-04T11:37:45Z
dc.date.issued2025-03-21en
dc.description.abstractAs the effects of climate change are increasingly felt worldwide, the transition to Electric Buses (EB) presents an opportunity to decarbonize the transportation sector. Several issues exist that hinder the adoption of a green bus f leet. Such as the increased cost, reduced travel distances, and required recharge times, which may negatively impact service quality. This work proposes a Mixed Integer Programming model to solve a multi-objective mixed fleet charging schedule problem. The mixed fleet considers EBs and Internal Combustion Engine Buses (ICEBs) and minimizes daily costs, such as fuel price, the Social Cost of Carbon (SCC) produced by the bus fleet, and the Value of Time (VoT) of public transport users. Non-linear charging is considered as well as alternative approaches along with Time of Use (TOU) constraints for electricity price and SCC. Empirical evaluation shows that significant savings can be made, with reductions of over €20000 in fuel costs, and reductions of over 100 tCO2eq per day. Consideration of VoT minimizes negative customer impact, limiting late arrivals to an average of 8.78 seconds per EB. The inclusion of non-linear charging makes minimal positive impact compared to limiting the total capacity of the battery, and while the inclusion of TOU constraints correlates to more savings, the amount saved is minute.en
dc.description.statusPeer revieweden
dc.description.versionPublished Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationJarvis, P., Climent, L. and Arbelaez, A. (2024) 'Multi-objective mixed bus fleet charging schedule problem with Time-of-Use for real-world data-sets', Proceedings of the 32nd Irish Conference on Artificial Intelligence and Cognitive Science (AICS 2024), Dublin, Ireland, 9-10 December, pp. 241-253. Available at: https://ceur-ws.org/Vol-3910/en
dc.identifier.endpage253en
dc.identifier.issn1613-0073en
dc.identifier.startpage241en
dc.identifier.urihttps://hdl.handle.net/10468/17236
dc.language.isoenen
dc.publisherCEUR-WS.orgen
dc.relation.ispartof32nd Irish Conference on Artificial Intelligence and Cognitive Science (AICS 2024)en
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres/12/RC/2289/IE/INSIGHT - Irelands Big Data and Analytics Research Centre/en
dc.relation.urihttps://ceur-ws.org/Vol-3910/en
dc.rights© 2024, the Authors.en
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subjectMulti-objectiveen
dc.subjectMixed fleeten
dc.subjectTime of useen
dc.subjectSchedulingen
dc.subjectElectric busen
dc.titleMulti-objective mixed bus fleet charging schedule problem with Time-of-Use for real-world data-setsen
dc.typeConference itemen
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