Collaborative strategic and tactical planning for one-way station-based carsharing systems with trip selection and vehicle relocation

ABSTRACT

Carsharing emerges as a flexible and sustainable transportation mode to deal with severe urban challenges. This paper addresses a joint design problem of carsharing systems by an integer linear programming (ILP) model. Strategic planning of stations’ number, location and parking capacities and tactical planning of the fleet size and initial vehicle distribution are collaboratively optimized by considering all-day vehicle relocation and dynamic trip selection at the operational level. For the first time, vehicle relocation and demand selection are integrated with the joint optimization of strategic and tactical planning. We present a greedy heuristic algorithm embedding ILP to solve the problem. The case study of Chengdu demonstrates that the algorithm is computationally efficient when dealing with large-scale problems. The results identify how vehicle relocation and trip selection work in different scenes of travel time and demands and we conclude operators should target at medium-long trips by discount or promotion.

KEYWORDS:

• Carsharing
• location model
• trip selection
• vehicle relocation
• greedy algorithm
• integer linear programming

Disclosure statement

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

Additional information

Funding

This work was supported by the National Natural Science Foundation of China under Grant [No. 71901183] and the Applied Basic Research Programs of Science and Technology Department of Sichuan Province [No. 2021YJ0066]. The authors are responsible for any remaining errors.