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

Sara Hatami, Majid Eskandarpour, Manuel Chica, Angel A. Juan*, Djamila Ouelhadj

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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-rangecapabilities, 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 alternativefleet 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.

Original languageEnglish
Pages (from-to)141-170
Number of pages30
JournalSORT
Volume44
Issue number1
DOIs
Publication statusPublished - 1 Jun 2020

Keywords

  • Electric Vehicles
  • Heterogeneous Fleet
  • Iterated Greedy heuristic
  • Multiple Driving Ranges
  • Successive Approximations Method
  • Vehicle Routing Problem

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