Title: A hybrid genetic algorithm for battery swap stations location and inventory problem

Authors: Jun Yang; Hao Sun

Addresses: School of Management, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, China ' School of Management, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, China

Abstract: This paper studies the electric vehicles battery swap station location and inventory problem (EV-LIP) which determines the location and battery inventory of battery swap stations. The EV-LIP is formulated as an integer program with deterministic traffic flow and a modified genetic algorithm (GA) is implemented. Next, a chance constrained function is constructed to extend the model with stochastic traffic flow and a simulation procedure is embedded into the GA. The results of comparative experiments show that the algorithm performs well. Moreover, the model is applied to a practical network and sensitivity analyses on driving range and service level are discussed.

Keywords: battery swap stations; facility location; battery inventory; chance-constrained modelling; genetic algorithms; electric vehicles; stochastic traffic flow; simulation; driving range; service levels.

DOI: 10.1504/IJSTL.2015.069122

International Journal of Shipping and Transport Logistics, 2015 Vol.7 No.3, pp.246 - 265

Accepted: 27 Mar 2014
Published online: 29 Apr 2015 *

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