Location of electric vehicle charging stations under uncertainty on the driving range

Mouna Kchaou Boujelben, Celine Gicquel

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


We study the problem of locating electric vehicle (EV) charging stations on road networks. We consider that the driving range, i.e. the maximum distance that a fully charged EV can travel before its battery runs empty, is subject to uncertainty and seek to maximize the expected coverage of the recharging demand. We first propose a new mixed-integer linear programming formulation for this stochastic optimization problem and compare it with a previously published one. We then develop a tabu search heuristic procedure to solve large-size instances of the problem. Our numerical experiments show that the new formulation leads to a better performance than the existing one and that the tabu search heuristic provides good quality solutions within short computation times.

Original languageEnglish
Title of host publicationComputational Logistics - 9th International Conference, ICCL 2018, Proceedings
EditorsRaffaele Cerulli, Andrea Raiconi, Stefan Voß
PublisherSpringer Verlag
Number of pages12
ISBN (Print)9783030008970
Publication statusPublished - 2018
Event9th International Conference on Computational Logistics, ICCL 2018 - Vietri sul Mare, Italy
Duration: Oct 1 2018Oct 3 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11184 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference9th International Conference on Computational Logistics, ICCL 2018
CityVietri sul Mare


  • Electric vehicle charging station network design
  • Flow refueling location problem
  • Mixed-integer linear programming
  • Stochastic driving range
  • Tabu search

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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