Raeesi, Ramin, Zografos, Konstantinos G. (2021) Coordinated routing of electric commercial vehicles with intra-route recharging and en-route battery swapping. European Journal of Operational Research, . ISSN 0377-2217. (KAR id:90454)
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Language: English
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Official URL: https://doi.org/10.1016/j.ejor.2021.09.037 |
Resource title: | EVRPTW-RS-SMBS |
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Resource type: | Dataset |
DOI: | 10.22024/UniKent/01.01.400 |
KDR/KAR URL: | https://data.kent.ac.uk/400/ |
External URL: | https://data.kent.ac.uk/400/ |
Abstract
A primary challenge in goods distribution using Electric Commercial Vehicles (ECVs) pertains to tackling their limited driving range. This paper proposes a multi-faceted approach towards increasing the driving range of ECVs by coordinating the options of: (i) intra-route recharging at an intermediate Recharging Station (RS), with (ii) synchronised en-route battery swapping services performed by Battery Swapping Vans (BSVs) at a pre-planned rendezvous time and space. We introduce and solve a variant corresponding to an Electric Vehicle Routing Problem with Time Windows, RSs and Synchronised Mobile Battery Swapping (EVRPTW-RS-SMBS). In the proposed model, route planning is carried out synchronously for two interdependent fleets, i.e., ECVs and BSVs, which work in tandem to complete the delivery tasks. To address methodological complications arising from the simultaneous consideration of intra-route recharging at RSs and the synchronised battery swapping on-the-fly, the paper develops a pre-optimisation procedure based on a Non-Dominated Path Identification (NDPI) algorithm that is used in deriving a significantly strengthened path-based formulation of the problem, and an efficient dynamic programming based heuristic algorithm. To gain practical insights on the economic and environmental added value and viability of the proposed logistics model, we compare different scenarios for goods distribution using ECVs in urban and regional levels in London and Southeast England, respectively. A set of numerical experiments are further performed to demonstrate the efficiency of the proposed algorithms. Our results indicate significant cost and emissions savings and an opportunity for going beyond last mile local deliveries using ECVs with the proposed logistics model.
Item Type: | Article |
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Uncontrolled keywords: | Routing; Electric Vehicles; Recharging; Battery Swapping; Scheduling and Synchronisation |
Subjects: | H Social Sciences > HE Transportation and Communications |
Divisions: | Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems |
Depositing User: | Ramin Raeesi |
Date Deposited: | 05 Oct 2021 19:52 UTC |
Last Modified: | 03 Oct 2023 23:00 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/90454 (The current URI for this page, for reference purposes) |
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