Joint Inventory-Routing Optimization for Battery Swapping Networks

Abstract

The rapid expansion of electric vehicle battery-swapping networks is increasing pressure on urban power grids. We study a hybrid battery swapping-charging system with multiple local swapping stations (SSs) and one central charging station (CS). Depleted batteries are either charged at SSs or transported to the CS for centralized charging and periodic redistribution. A joint inventory-routing problem is formulated to optimize replenishment policies and delivery routes, minimizing total cost under service-level constraints. By characterizing battery deficit processes at the CS and SSs, we derive closed-form expressions for their first two moments, yielding tractable inventory policies. To solve the resulting problem efficiently, we exploit the submodular cost structure under knapsack constraints, derive facet-defining extended polymatroid inequalities (EPIs), and develop enhanced EPIs for a customized branch-and-cut framework. Real-data case studies show that, for large-scale instances, enhanced EPIs reduce average solution time by about 52% and 83% relative to improved EPIs and classical EPIs. Under practical settings, hybrid charging reduces total cost by 3.12% and 3.79% compared with fully centralized and fully decentralized charging, respectively. Depending on network characteristics such as station dispersion, on‑site charging capacity, and transportation cost, hybrid charging is preferable in moderate scenarios while fully centralized or decentralized charging becomes favourable in more extreme cases.

Event details

Presenter: Associate Professor Long He, George Washington University

Date: Tuesday, 19 May 2026

Time: 11:30 am – 12:30 pm

Venue: OGGB, Level 3, Room 260-321

Bio

Long He is an associate professor of decision sciences at the School of Business, George Washington University. Prior to joining GW, Long was an associate professor in the Department of Analytics & Operations at NUS Business School, National University of Singapore. He received his Ph.D. in Operations Research from the University of California, Berkeley, and his B.Eng. in Logistics Management and Engineering from HKUST. His current research combines data-driven optimization and ML/AI to address practical problems in smart city operations, sustainable energy systems, and supply chain management. This line of research has been recognized with the M&SOM Journal Best Paper Award, TSL Best Paper Award, the ENRE Best Publication Awards in Energy and in Natural Resources, and the Daniel H. Wagner Prize from INFORMS. He currently serves as an Associate Editor for Manufacturing & Service Operations Management (M&SOM) and Omega.

We look forward to greeting you at the seminar.

Best regards,

Dr Sarah Marshall
Director, CSCM

auckland.ac.nz/cscm

Associate Professor Long He, George Washington University

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