Integrated Multi-Modal Logistics Planning and Scheduling for Electric Freight Systems

As global supply chains increasingly prioritize environmental sustainability and operational efficiency, battery electric freight vehicles (EFVs) have emerged as a pivotal alternative to traditional diesel-powered logistics fleets. This paper addresses the integrated planning and scheduling problem for multi-modal logistics systems utilizing EFVs. An integrated model is proposed to determine the number of electric freight vehicles and optimize dispatch and charging schedules, considering deadheading, and time-of-use electricity pricing. The model is formulated as an integer linear programming (ILP) problem solvable by commercial solvers. A branch-and-price framework and a heuristic algorithm are developed to handle large-scale instances. A case study using real data from a logistics provider in China demonstrates that the EFV system achieves a 45.5% reduction in total monthly costs compared to traditional diesel freight vehicle systems, even after accounting for higher vehicle and infrastructure costs. Sensitivity analyses offer practical insights for EFV adoption in multi-modal logistics.