The Bike-Sharing Rebalancing Problem Considering Multi-Energy Mixed Fleets and Traffic Restrictions

Yongji Jia, Wang Zeng, Yanting Xing, Dong Yang and Jia Li
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Yongji Jia: Glorious Sun School of Business & Management, Donghua University, Shanghai 200051, China
Wang Zeng: Glorious Sun School of Business & Management, Donghua University, Shanghai 200051, China
Yanting Xing: Glorious Sun School of Business & Management, Donghua University, Shanghai 200051, China
Dong Yang: Glorious Sun School of Business & Management, Donghua University, Shanghai 200051, China
Jia Li: Glorious Sun School of Business & Management, Donghua University, Shanghai 200051, China

Sustainability, 2020, vol. 13, issue 1, 1-15

Abstract: Nowadays, as a low-carbon and sustainable transport mode bike-sharing systems are increasingly popular all over the world, as they can reduce road congestion and decrease greenhouse gas emissions. Aiming at the problem of the mismatch of bike supply and user demand, the operators have to transfer bikes from surplus stations to deficiency stations to redistribute them among stations by vehicles. In this paper, we consider a mixed fleet of electric vehicles and internal combustion vehicles as well as the traffic restrictions to the traditional vehicles in some metropolises. The mixed integer programming model is firstly established with the objective of minimizing the total rebalancing cost of the mixed fleet. Then, a simulated annealing algorithm enhanced with variable neighborhood structures is designed and applied to a set of randomly generated test instances. The computational results and sensitivity analysis indicate that the proposed algorithm can effectively reduce the total cost of rebalancing.

Keywords: sustainable transport; bike-sharing rebalancing problem; multi-energy mixed fleets; traffic restrictions; simulated annealing; variable neighborhood structures (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
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