Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

4-2019

Abstract

Electric Vehicles (EVs) are the next wave of technology in the transportation industry. EVs are increasingly becoming common for personal transport and pushing the boundaries to become the mainstream mode of transportation. Use of such EVs in logistic fleets for delivering customer goods is not far from becoming reality. However, managing such fleet of EVs bring new challenges in terms of battery capacities and charging infrastructure for efficient route planning. Researchers have addressed such issues considering different aspects of the EVs such as linear battery charging/discharging rate, fixed travel times, etc. In this paper, we address the issue of waiting times due to limited charging capacity at the charging stations while planning the routes of EVs for providing pickup/delivery services. We provide an exact mathematical model of the problem considering waiting times of vehicle based on their arrival at the charging stations. We further develop a genetic algorithm approach that embeds Constraint Programming to solve the problem. We test our approach on a set of benchmark Solomon instances.

Keywords

Constraint Programming, Electric Vehicle Routing Problem, Genetic algorithm, Mixed integer linear programming

Discipline

Artificial Intelligence and Robotics | Operations Research, Systems Engineering and Industrial Engineering | Transportation

Research Areas

Intelligent Systems and Optimization

Publication

Evolutionary computation in combinatorial optimization: 19th European Conference, EvoCOP 2019, Leipzig, Germany, April 24-26, 2019: Proceedings

Volume

11452

First Page

66

Last Page

82

ISBN

9783030167103

Identifier

10.1007/978-3-030-16711-0_5

Publisher

Springer

City or Country

Cham

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1007/978-3-030-16711-0_5

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