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


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.

Publication DOI: https://doi.org/10.1016/j.jclepro.2019.117687
Divisions: College of Engineering & Physical Sciences > School of Engineering and Technology > Mechanical, Biomedical & Design
College of Engineering & Physical Sciences
Additional Information: © 2019, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Uncontrolled Keywords: Continuous optimization,Electric vehicle routing problem,Mixed-integer linear programming,Nonlinear charging function,Renewable Energy, Sustainability and the Environment,Environmental Science(all),Strategy and Management,Industrial and Manufacturing Engineering
Publication ISSN: 1879-1786
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Related URLs: https://linking ... 959652619325375 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2019-11-01
Published Online Date: 2019-07-17
Accepted Date: 2019-07-15
Authors: Zuo, Xiaorong
Xiao, Yiyong
You, Meng
Kaku, Ikou
Xu, Yuchun (ORCID Profile 0000-0001-6388-813X)

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