Location of Electric Vehicle Charging Stations Under Uncertainty on the Driving Range

  • Mouna Kchaou BoujelbenEmail author
  • Celine Gicquel
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11184)


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.


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


  1. 1.
    Tweed, K.: Fast charging key to electric vehicle adoption. Accessed 18 Mar 2018
  2. 2.
    Kuby, M., Lim, S.: The flow-refueling location problem for alternative-fuel vehicles. Socio-Econ. Plan. Sci. 39, 125–145 (2005)CrossRefGoogle Scholar
  3. 3.
    Upchurch, C., Kuby, M., Lim, S.: A model for location of capacitated alternative-fuel stations. Geogr. Anal. 41(1), 85–106 (2009)CrossRefGoogle Scholar
  4. 4.
    Kim, J.G., Kuby, M.: The deviation-flow refueling location model for optimizing a network of refueling stations. Int. J. Hydrogen Energy 37, 5406–5420 (2012)CrossRefGoogle Scholar
  5. 5.
    Lim, S., Kuby, M.: Heuristic algorithms for siting alternative-fuel stations using the flow-refueling location model. Eur. J. Oper. Res. 204, 51–61 (2010)CrossRefGoogle Scholar
  6. 6.
    Lee, C., Han, J.: Benders-and-price approach for electric vehicle charging station location problem under probabilistic travel range. Transp. Res. Part B 106, 130–152 (2017)CrossRefGoogle Scholar
  7. 7.
    De Vries, H., Duijzer, E.: Incorporating driving range variability in network design for refueling facilities. Omega 69, 102–114 (2017)CrossRefGoogle Scholar
  8. 8.
    Capar, I., Kuby, M., Leon, V.J., Tsai, Y.-J.: An arc-cover path-cover formulation and strategic analysis of alternative-fuel station locations. Eur. J. Oper. Res. 227, 142–151 (2013)CrossRefGoogle Scholar
  9. 9.
    Fotheringham, A., O’Kelly, M.: Spatial Interaction Models: Formulations and Applications. Kluwer Academic Publishers, Dordrecht (1989)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.College of Business and EconomicsUAE UniversityAl AinUnited Arab Emirates
  2. 2.LRI, Université Paris-SaclayOrsayFrance

Personalised recommendations