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Research Article

Electric bus scheduling with the self-adaptive charging strategy based on a course selection idea

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Article: 2170719 | Received 24 Jun 2022, Accepted 17 Jan 2023, Published online: 03 Feb 2023
 

Abstract

This paper investigates the electric bus scheduling problem, aiming to design collaborative service and charging schedules. A self-adaptive charging strategy is introduced, allowing electric buses to be recharged partially and flexibly. Then, a mixed-integer programme model is built for the problem, based on a course selection idea that considers continuous time. Two models for scenarios considering prior greedy and full charging strategies are also established for comparison. Next, a greed-based branch-and-price algorithm is developed for model solving, which incorporates a greedy attachment heuristic for the initialisation and a customised branching scheme based on the course flow. The results of a case study in Beijing show the efficiency of the proposed algorithm and the superiority of the self-adaptive charging strategy. Compared with the two prior charging strategies, the average energy replenishment of electric buses is reduced by 22.47% and 35.99%, and the system cost is reduced by 5.47% and 5.60%.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research was supported by the National Natural Science Foundation of China (Nos. 72171020, 71890972/71890970, 72288101) and the 111 Project (No. B20071). Besides, the author thanks Jianhua Chen of Shenzhen Polytechnic, Shenzhen, China, for his help in writing-review and editing.

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