Optimizing battery electric bus allocations: an integrated approach to cost minimization and evolutionary game theory
Document Type
Journal Article
Publication Date
2026
Subject Area
place - asia, place - urban, mode - bus, infrastructure - fleet management, operations - frequency, operations - scheduling, economics - capital costs, technology - alternative fuels
Keywords
Battery electric bus, transit operations optimization, fleet sizing and allocation, hybrid charging strategy, evolutionary game theory
Abstract
High capital costs and vehicle allocation challenges impede urban public transport electrification. This paper presents an integrated optimization framework for battery electric bus (BEB) fleet scheduling under both opportunity and depot charging conditions, simultaneously optimizing battery capacity, dispatch frequency, and fleet size to minimize total annualized system cost. A hybrid heuristic algorithm achieves high-quality solutions within practical runtimes. An evolutionary game model captures dynamic interactions between operators and passengers under alternative allocation strategies. The framework is validated through a case study in Harbin, China. Results demonstrate that the optimal configuration reduces annualized system cost by approximately 17.8% (≈266 million CNY) relative to the baseline and identifies cost-effective combinations of key decision variables. Sensitivity analyses confirm robustness across varying wireless charging facility scenarios. These findings provide actionable insights for electric bus planning and sustainable fleet management in cold-climate urban environments.
Rights
Permission to publish the abstract has been given by Taylor&Francis, copyright remains with them.
Recommended Citation
Liu, J., Zhang, J., Dong, C., & He, Q. (2026). Optimizing battery electric bus allocations: an integrated approach to cost minimization and evolutionary game theory. Transportation Letters, 18(3), 636-669.
