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

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Abstract

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.

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APA

Kchaou Boujelben, M., & Gicquel, C. (2018). Location of electric vehicle charging stations under uncertainty on the driving range. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11184 LNCS, pp. 475–486). Springer Verlag. https://doi.org/10.1007/978-3-030-00898-7_32

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