Journal article
Integrated Electric Bus and Charger Scheduling With Time-Continuous Optimization and Efficient Combinational Algorithms
IEEE transactions on intelligent transportation systems, pp 1-22
18 Dec 2025
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Battery electric buses (BEBs) are increasingly adopted in urban transit systems due to their significant environmental benefits. However, their limited driving range and prolonged charging times introduce significant operational challenges. To address these issues, this study investigates an integrated bus and charger scheduling problem through a time-continuous optimization framework. The problem incorporates key operational considerations, including time-of-use electricity pricing, partial charging strategy, nonlinear battery charging profile, stochastic trip durations and energy consumption, and a limited number of chargers. A mixed-integer model is formulated on a specially constructed two-layer trip-charging integrated scheduling network to minimize the total system cost. To effectively solve the problem, a two-stage solution approach is developed for the charger scheduling subproblem, which employs a minimum-cost-maximum-flow-based algorithm to determine the charging durations under TOU pricing, followed by a deficit-function-based heuristic to optimize charging start times. Building on this, two solution frameworks - branch-and-bound (BB) and adaptive large neighborhood search (ALNS) - are developed to solve the integrated scheduling problem. Computational experiments demonstrate that the BB approach consistently outperforms the commercial solver Gurobi, yielding superior solutions within similar or shorter computational times. Meanwhile, the ALNS delivers high-quality solutions with significantly lower computational effort, making it well-suited for large-scale real-world applications.
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Details
- Title
- Integrated Electric Bus and Charger Scheduling With Time-Continuous Optimization and Efficient Combinational Algorithms
- Creators
- Jie Xiong - Beijing University of TechnologyJingjing Liang - Beijing University of TechnologyTongfei Li - Beijing University of TechnologyZhiwei Chen - Drexel UniversityWei Guan - Beijing Jiaotong University
- Publication Details
- IEEE transactions on intelligent transportation systems, pp 1-22
- Publisher
- IEEE
- Number of pages
- 22
- Grant note
- 8252003 / Beijing Natural Science Foundation (10.13039/501100005089) 71901007; 71601006 / National Natural Science Foundation of China (10.13039/501100001809)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Civil, Architectural, and Environmental Engineering
- Web of Science ID
- WOS:001643576300001
- Scopus ID
- 2-s2.0-105025455265
- Other Identifier
- 991022148194704721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Engineering, Civil
- Engineering, Electrical & Electronic
- Transportation Science & Technology