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Title: Green hybrid fleets using electric vehicles: solving the heterogeneous vehicle routing problem with multiple driving ranges and loading capacities
Author: Hatami, Sara
Eskandarpour, Majid
Chica Serrano, Manuel
Juan Pérez, Ángel Alejandro
Ouelhadj, Djamila
Others: Universitat Oberta de Catalunya. Internet Interdisciplinary Institute (IN3)
Universidad de Granada
University of Portsmouth
Université de Lille
Keywords: vehicle routing problem
electric vehicles
heterogeneous fleets
multiple driving ranges
successive approximations method
Issue Date: Jan-2020
Publisher: SORT: Statistics and Operations Research Transactions
Citation: Hatami, S., Eskandarpour, M., Chica, M., Juan, A. A. & Ouelhadj, D. (2020). Green hybrid fleets using electric vehicles: solving the heterogeneous vehicle routing problem with multiple driving ranges and loading capacities. SORT: Statistics and Operations Research Transactions, 44 (1), 141-170. doi: 10.2436/20.8080.02.98
Project identifier: info:eu-repo/grantAgreement/RED2018-102642-T
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Abstract: The introduction of Electric Vehicles (EVs) in modern fleets facilitates green road transportation. However, the driving ranges of EVs are limited by the duration of their batteries, which arise new operational challenges. Hybrid fleets of gas and EVs might be heterogeneous both in loading capacities as well as in driving-range capabilities, which makes the design of efficient routing plans a difficult task. In this paper, we propose a new Multi-Round Iterated Greedy (MRIG) metaheuristic to solve the Heterogeneous Vehicle Routing Problem with Multiple Driving ranges and loading capacities (HeVRPMD). MRIG uses a successive approximations method to offer the decision maker a set of alternative fleet configurations, with different distance-based costs and green levels. The numerical experiments show that MRIG is able to outperform previous works dealing with the homogeneous version of the problem, which assumes the same loading capacity for all vehicles in the fleet. The numerical experiments also confirm that the proposed MRIG approach extends previous works by solving a more realistic HeVRPMD and provides the decision-maker with fleets with higher green levels.
ISSN: 1696-2281MIAR
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