Fleet sizing and dynamic relocation problems for electric kick scooter sharing system

Abstract

Electric kick-scooters (EKSs) have emerged as a promising solution to address first- and last-mile challenges in urban transportation. This paper presents an operational design framework that sequentially addresses fleet sizing and dynamic relocation problems to optimize operational performance. The fleet sizing problem aims to determine the minimal EKS fleet size and initial distribution required to achieve a predefined service level without considering battery charging or EKS relocations. The results indicate that fleet size increases with higher battery consumption per rental and elevated service level requirements. Three dynamic relocation strategies—truck-only, crowdsourcing-only, and hybrid—are modeled using a time-space network formulation to enhance system efficiency. Numerical analyses demonstrate that each relocation strategy significantly improves service levels compared to a non-relocation baseline. However, the maximum achievable service level is constrained by the initial fleet size and available relocation resources, and deploying extensive relocation resources for a smaller fleet cannot match the service rate improvements achievable through a larger EKS fleet. The results provide practical guidance for shared EKS operators, showing that hybrid relocation strategies can improve service performance under operational constraints. Among the three strategies, hybrid relocation consistently outperforms truck-only and crowd-only approaches when moderate relocation capacity is available.