Abstract
With soaring fuel prices and the imperative to reduce global carbon emissions, electric vehicles (EVs) possess unparalleled advantages in terms of sustainability. Consequently, numerous express service providers have commenced the implementation of EV-based express service networks. However, designing an effective service network for EV fleets necessitates considering recharging operations during the route planning process. In this study, we explore a problem involving the design of an EV-based express service network under the constraint of limited recharging resources, while taking into account power management for each EV throughout the entire operational cycle. To address this challenge, we present a mixed-integer optimization model incorporating a Dantzig–Wolfe reformulation. Additionally, we develop resource extension functions that enable an efficient dynamic labeling algorithm, incorporating dominance rules, to solve complex subproblems. We propose a branch-and-price framework that integrates an aggregated branching strategy and a heuristic upper-bound technique, enabling the attainment of exact solutions for instances involving large fleet sizes. Computational experiments conducted on realistic instances, involving up to 20 terminals and over 2000 EVs, substantiate the efficiency of our approach.
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