Double-balanced relocation optimization of one-way car-sharing system with real-time requests

One-way car-sharing systems, an increasingly prominent transportation means, are facing the vehicle imbalance issue with their emergence. To overcome the problem, operators have adopted a common strategy to relocate vehicles among stations by dispatchers. However, along with this approach come imbalanced dispatchers, demanding double-balanced optimization for relocation operations in vehicle relocation and dispatcher scheduling. In this paper, we propose an integrated model to determine the optimal requests served, relocation tasks, and dispatchers? routes in order to minimize the generalized daily operational cost. The model adopts two different time granularities to obtain all the possible relocation tasks and the refined scheduling of dispatchers. Due to the dynamic nature and the scale of this double-balanced relocation problem, a hybrid solution algorithm is designed combining a rolling horizon algorithm with a customized decomposition algorithm. The planning horizon consists of several stages, each of which contains a sub-problem for the double-balanced relocation, and a customized decomposition is embedded to optimize it efficiently. Some computational experiments and a case study in Lanzhou, China are conducted to identify critical parameters and illustrate the performance of the proposed method.

Automated summary

This study proposes an integrated model to optimize task service, relocation tasks, and dispatcher routes in one-way car-sharing systems to minimize daily operational costs. The model uses two different time granularities to obtain all possible tasks and refine dispatcher scheduling.