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Priority-based multi-task scheduling for shared micro-mobility systems
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DOI：10.1016/j.trc.2026.105796.png)
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Abstract
En 中文
Shared micro-mobility systems advance sustainable transport by promoting environmentally friendly travel while enhancing convenience, accessibility, and operational efficiency. Most existing literature focuses primarily on vehicle rebalancing to improve shared micro-mobility system efficiency. However, system effectiveness cannot be achieved through rebalancing alone without ensuring reliable maintenance operations and battery functionality. To address these integrated challenges, this paper proposes a multi-task scheduling framework that unifies vehicle rebalancing, maintenance, battery replacement, and priority-based resource allocation mechanisms. We formulate a Mixed-Integer Programming (MIP) model and employ an Adaptive Large Neighborhood Search (ALNS) heuristic with customized operators to manage computational complexity effectively. Numerical experiments conducted on instances with varying request volumes demonstrate the superior performance of the proposed framework. The multi-task scheduling approach incorporating maintenance and battery replacement significantly outperforms single-task methodologies, substantially improving both availability and service rates of shared vehicles. We explore a range of high-priority request ratios, revealing the inherent trade-offs between service quality and operational cost. We further evaluate model performance under both concentrated and dispersed inventory-demand distribution scenarios. These findings provide practical insights for shared micro-mobility operators in designing strategic fleet deployment, optimizing rebalancing schedules, and allocating maintenance and battery resources effectively under diverse demand patterns and operational conditions.
Keywords:
Sustainable urban mobility
Shared micro-mobility
Multi-commodity vehicle rebalancing
Multi-task scheduling
Adaptive large neighborhood search
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