Vehicle relocation and staff rebalance problem in one-way free-floating car-sharing system: A novel multi-iteration probabilistic greedy algorithm

Abstract

This research aims to address the staff-based vehicle relocation problem that arises in a one-way car-sharing system operating in a combined mode, in which both on-street parking slots and parking hubs are utilized. The objective of the problem is to determine the relocation plan for vehicles and travel routes for staff with the minimum operational costs. A novel mathematical model is proposed to control the model size, in which the parking spaces constraint is considered without introducing dummy nodes. Then, based on the structure of the model, a heuristic algorithm with tailored operators and the initial solution generation method is proposed to solve the problem. The experimental results demonstrate that, with the tailored operators and solving strategies, the proposed method outperforms commercial solvers and other existing heuristic algorithms in terms of both solving efficiency and solution quality. Furthermore, a group of test cases generated from real cases is utilized to examine the performance of the relocation plan in different scenarios. The results indicate that the overall operation costs of the car-sharing system could be effectively controlled by distributing parking capacities among parking hubs evenly. In addition, the proposed model and high-efficiency algorithm also enable decision-makers to test the performance of the car-sharing system in various scenarios and help them to get a better understanding of the system.