Green hybrid fleets using electric vehicles: solving the heterogeneous vehicle routing problem with multiple driving ranges and loading capacities

IF 0.7 4区数学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

Sort-Statistics and Operations Research Transactions Pub Date : 2020-06-01 DOI:10.2436/20.8080.02.98

Sara Hatami, M. Eskandarpour, M. Serrano, Ángel Alejandro Juan Pérez, D. Ouelhadj

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引用次数: 9

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,whichmakes the design of efficient routing plans a difficult task. In this paper, we propose a newMulti-Round IteratedGreedy (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.

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使用电动汽车的绿色混合动力车队:解决多行驶里程和多载重能力的异构车辆路径问题

电动汽车(ev)在现代车队中的引入促进了绿色道路交通。然而，电动汽车的行驶里程受到电池续航时间的限制，这带来了新的运营挑战。汽油和电动汽车的混合动力车队在装载能力和行驶里程方面可能存在差异，这使得设计有效的路线规划成为一项艰巨的任务。本文提出了一种新的多轮迭代贪心(MRIG)元启发式算法来解决具有多行驶里程和负载能力的异构车辆路由问题(HeVRPMD)。MRIG使用连续逼近方法为决策者提供一组可选的车队配置，这些配置具有不同的基于距离的成本和绿色水平。数值实验表明，MRIG算法能够优于以往的同质版本算法，即假设车队中所有车辆的装载能力相同。数值实验也证实了所提出的MRIG方法通过解决更现实的HeVRPMD而扩展了先前的工作，并为决策者提供了更高绿色水平的车队。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Sort-Statistics and Operations Research Transactions 管理科学-统计学与概率论

CiteScore

3.10

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： SORT (Statistics and Operations Research Transactions) —formerly Qüestiió— is an international journal launched in 2003. It is published twice-yearly, in English, by the Statistical Institute of Catalonia (Idescat). The journal is co-edited by the Universitat Politècnica de Catalunya, Universitat de Barcelona, Universitat Autonòma de Barcelona, Universitat de Girona, Universitat Pompeu Fabra i Universitat de Lleida, with the co-operation of the Spanish Section of the International Biometric Society and the Catalan Statistical Society. SORT promotes the publication of original articles of a methodological or applied nature or motivated by an applied problem in statistics, operations research, official statistics or biometrics as well as book reviews. We encourage authors to include an example of a real data set in their manuscripts.