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Charging scheduling optimisation of battery electric buses with charging setup time.

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Title: Charging scheduling optimisation of battery electric buses with charging setup time.
Authors: Wang, Zhixin1 (AUTHOR), Zheng, Feifeng1 (AUTHOR), Hamdan, Sadeque2 (AUTHOR) s.hamdan@bangor.ac.uk, Jouini, Oualid3 (AUTHOR)
Source: International Journal of Production Research. May2025, Vol. 63 Issue 10, p3538-3563. 26p.
Subjects: Setup time, Sustainable transportation, Electric motor buses, Electric batteries, Electric charge
Abstract: Battery electric buses (BEBs) are recognised as sustainable modes of transportation. Because of its increasing range, efficient and convenient overnight charging has become crucial. The limited number of charging stations and variability in setup times require the optimisation of BEB charging schedules. This study proposes an optimal overnight centralised charging schedule that considers setup time and battery-degradation costs. We model this as a multi-travelling salesman problem with sojourn time to minimise operating costs, including electricity, setup time, and battery wear, while adhering to the bus-schedule constraints. We introduce a local search grouping genetic algorithm with a 2-opt operator local search to address the complexities of public-transport networks. Our extensive numerical analysis, grounded in real-world data, shows a 4.48% reduction in operating costs using our optimised strategy compared with current methods. Moreover, our charging-station allocation analysis provides insights for resource optimisation, advancing sustainable public transport, and charging strategies. This study contributes to the field of sustainable public transportation and charging optimisation. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Charging scheduling optimisation of battery electric buses with charging setup time.
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  Data: <searchLink fieldCode="AR" term="%22Wang%2C+Zhixin%22">Wang, Zhixin</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zheng%2C+Feifeng%22">Zheng, Feifeng</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hamdan%2C+Sadeque%22">Hamdan, Sadeque</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> s.hamdan@bangor.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Jouini%2C+Oualid%22">Jouini, Oualid</searchLink><relatesTo>3</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Production+Research%22">International Journal of Production Research</searchLink>. May2025, Vol. 63 Issue 10, p3538-3563. 26p.
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  Data: <searchLink fieldCode="DE" term="%22Setup+time%22">Setup time</searchLink><br /><searchLink fieldCode="DE" term="%22Sustainable+transportation%22">Sustainable transportation</searchLink><br /><searchLink fieldCode="DE" term="%22Electric+motor+buses%22">Electric motor buses</searchLink><br /><searchLink fieldCode="DE" term="%22Electric+batteries%22">Electric batteries</searchLink><br /><searchLink fieldCode="DE" term="%22Electric+charge%22">Electric charge</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Battery electric buses (BEBs) are recognised as sustainable modes of transportation. Because of its increasing range, efficient and convenient overnight charging has become crucial. The limited number of charging stations and variability in setup times require the optimisation of BEB charging schedules. This study proposes an optimal overnight centralised charging schedule that considers setup time and battery-degradation costs. We model this as a multi-travelling salesman problem with sojourn time to minimise operating costs, including electricity, setup time, and battery wear, while adhering to the bus-schedule constraints. We introduce a local search grouping genetic algorithm with a 2-opt operator local search to address the complexities of public-transport networks. Our extensive numerical analysis, grounded in real-world data, shows a 4.48% reduction in operating costs using our optimised strategy compared with current methods. Moreover, our charging-station allocation analysis provides insights for resource optimisation, advancing sustainable public transport, and charging strategies. This study contributes to the field of sustainable public transportation and charging optimisation. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1080/00207543.2024.2424973
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 26
        StartPage: 3538
    Subjects:
      – SubjectFull: Setup time
        Type: general
      – SubjectFull: Sustainable transportation
        Type: general
      – SubjectFull: Electric motor buses
        Type: general
      – SubjectFull: Electric batteries
        Type: general
      – SubjectFull: Electric charge
        Type: general
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      – TitleFull: Charging scheduling optimisation of battery electric buses with charging setup time.
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            NameFull: Wang, Zhixin
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            NameFull: Zheng, Feifeng
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            NameFull: Hamdan, Sadeque
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            NameFull: Jouini, Oualid
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            – D: 15
              M: 05
              Text: May2025
              Type: published
              Y: 2025
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              Value: 63
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            – TitleFull: International Journal of Production Research
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