A new formulation of the electric vehicle routing problem with time windows considering concave nonlinear charging function

Xiaorong Zuo, Yiyong Xiao, Meng You, Ikou Kaku, Yuchun Xu

Research output: Contribution to journalArticle

Abstract

The electric vehicle routing problem with time window (EVRPTW) is an extension of the traditional vehicle routing problem with time window (VRPTW), where new features of electric vehicles are considered, such as limited battery capacities, lack of infrastructures, and long charging time. In this study, new technical formulations were presented for vehicle route selection and charging station visit, which reduces the formulation complexity without using duplicated dummy nodes or arcs. Besides, a new linearization method was developed that employs a set of secant lines to surrogate the concave nonlinear charging function with linear constraints. This method defines the charging time as a continuous variable and uses fewer variables than existing formulation in literature. A mixed-integer linear programming (MILP) model was developed for the EVRPTW and computational experiments on Solomon's VRPTW instances were conducted to verify the proposed model. The experimental results were compared with those obtained by traditional routing models, which showed that the proposed model can result in better EVs logistics schedules with higher charging time utilizations.
Original languageEnglish
Article number117687
JournalJournal of Cleaner Production
Volume236
Early online date17 Jul 2019
DOIs
Publication statusPublished - 1 Nov 2019

Bibliographical note

© 2019, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/

Keywords

  • Continuous optimization
  • Electric vehicle routing problem
  • Mixed-integer linear programming
  • Nonlinear charging function

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