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Electric bus charging scheduling on a bus network

  • Yu Zhou
  • , Qiang Meng*
  • , Ghim Ping Ong
  • , Hua Wang
  • *Corresponding author for this work
  • National University of Singapore
  • Hefei University of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

This study addresses the electric bus charging scheduling problem (EBCSP) within a bus network comprising multiple bus routes, depots, and a fleet of heterogeneous electric buses (EBs) operated by a public transport (PT) operator. The EBCSP aims to minimize total costs by concurrently determining the assignment of EBs to trips(i.e., EB-to-trip assignment) and their corresponding charging schedules. A partial charging policy allows for flexible charging durations, considering a published timetable consisting of trip tasks. We formulate the EBCSP as a mixed-integer linear programming model and a set-covering formulation. For small-scale EBCSPs, we propose a branch-and-price algorithm utilizing the set-covering formulation for exact solutions. As large-scale EBCSPs pose computational challenges, we develop an optimization-based adaptive large neighborhood search (opt-ALNS) method. The opt-ALNS method employs ALNS operators for EB-to-trip assignment and solves the remaining linear programming problem efficiently. To enhance the opt-ALNS process, we introduce a labeling method to assess solution feasibility and rebuild solutions. Moreover, we incorporate EB battery degradation effects into the proposed method. Finally, we assess the performance of the opt-ALNS method on real-life instances and compare it with the branch-and-price algorithm.

Original languageEnglish
Article number104553
JournalTransportation Research Part C: Emerging Technologies
Volume161
DOIs
StatePublished - Apr 2024

Keywords

  • Adaptive large neighborhood search method
  • Battery degradation
  • Branch-and-price algorithm
  • Bus network
  • Electric bus charging scheduling
  • Mixed-integer linear programming model
  • Set-covering model

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