Search Results (2)

The electric vehicle routing problem (EVRP) is constrained by the limited driving range and time-consuming energy replenishment. These characteristics shift the focus of the EVRP from simple path optimization to an integrated optimization of routing and energy replenishment. Consequently, the energy replenishment strategy becomes a critical determinant of the feasibility and economic viability of EVRP solutions. This paper presents a systematic literature review structured around a core classification of replenishment strategies. The strategies are categorized into two primary modes: charging and battery swapping. This framework addresses common gaps in existing research, such as imprecise strategy definitions and fragmented analyses. For the charging strategy, we establish a three-dimensional classification framework, which comprises the charging function, charging policy, and charging station type. Within this context, wireless charging is considered as a special method of energy replenishment. The battery swapping strategy relies on battery swapping stations (BSSs): the EVRP with BSSs (EVRP–BSSs) and the BSS location-routing problem with electric vehicle (BSS–EV–LRP). Our review identifies several limitations in the current body of research. These include an imbalance between modeling accuracy and computational efficiency, insufficient coverage of diverse operational scenarios, and a superficial integration of emerging technologies. Furthermore, many studies lack a multi-stakeholder perspective that considers collaborative solutions. Future research should prioritize addressing these gaps. Key directions include developing effective methods for solving nonlinear charging functions and expanding research into more specialized scenarios. Additionally, there is a need to improve collaborative algorithms for battery swapping and to develop shared BSS models that serve multiple enterprises. The strategy-driven framework proposed here offers a clear reference for modeling and scenario adaptation in future EVRP studies. Full article

The swap-body vehicle routing problem (SBVRP) represents a specialized extension of the traditional vehicle routing problem (VRP), incorporating additional practical complexities. Effective fuel consumption management and the scheduling of multiple vehicle trips are pivotal strategies for reducing costs and ensuring the sustainability of distribution systems. In response to the acceleration of urbanization, the rising demand for logistics, and the deteriorating living environment, we introduce an SBVRP considering fuel consumption and multiple trips to enable greener, cheaper, and more efficient delivery methods. To tackle the SBVRP, we propose a hybrid multi-population genetic algorithm enhanced with local search techniques to explore various areas of the search space. Computational experiments demonstrate the efficiency of the proposed method and the effectiveness of its components. The algorithm developed in this study provides an optimized solution to the VRP, focusing on achieving environmentally friendly, sustainable, and cost-effective transportation by reducing energy consumption and promoting the rational use of resources. Full article