Design of a Relocation Staff Assignment Scheme for Clustered Electric Vehicle Sharing Systems

This paper presents a design and evaluates the performance of a relocation staff allocation scheme for electric vehicle sharing systems, aiming at overcoming the stock imbalance problem and thus improving the service ratio. Basically, the relocation procedure moves vehicles from overflow stations to underflow stations according to the future demand estimation. For a given target distribution and the relocation pairs, the number of staff members for each cluster is decided to reduce relocation distance and time. The proposed scheme preliminarily runs the unit scheduler with minimal staff allocation to build an empirical distance estimation model. It repeats estimating the relocation cost for each cluster and assigning a staff member to the cluster having the worst relocation distance one by one. The performance measurement results show that the proposed scheme can reduce the relocation distance by up to 31.7 % compared with the even allocation scheme. It invokes the unit scheduler just twice, but achieves the performance comparable to the long loop scheme which runs the unit scheduler as many times as the number of staff members.