A Benders decomposition method for locating stations in a one-way electric car sharing system under demand uncertainty

Hatice Calik 1, 2 Bernard Fortz 1, 2
2 INOCS - Integrated Optimization with Complex Structure
ULB - Université Libre de Bruxelles [Bruxelles], Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Abstract : We focus on a problem of locating recharging stations in one-way station based electric car sharing systems which operate under demand uncertainty. We model this problem as a mixed integer stochastic program and develop a Benders decomposition algorithm based on this formulation. We integrate a stabilization procedure to our algorithm and conduct a large-scale experimental study on our methods. To conduct the computational experiments, we developed a demand forecasting method allowing to generate many demand scenarios. The method was applied to real data from Manhattan taxi trips. We are able to solve problems with 100 to 500 scenarios, each scenario including 1000 to 5000 individual customer requests, under high and low cost values and 5 to 15 mins of accessibility restrictions, which is measured as the maximum walking time to the operating stations.
Document type :
Preprints, Working Papers, ...
Complete list of metadatas

Cited literature [37 references]  Display  Hide  Download

https://hal.inria.fr/hal-01962059
Contributor : Bernard Fortz <>
Submitted on : Thursday, December 20, 2018 - 1:00:43 PM
Last modification on : Friday, April 19, 2019 - 4:54:58 PM
Long-term archiving on : Friday, March 22, 2019 - 1:00:33 PM

File

6486.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01962059, version 1

Collections

Citation

Hatice Calik, Bernard Fortz. A Benders decomposition method for locating stations in a one-way electric car sharing system under demand uncertainty. 2018. ⟨hal-01962059⟩

Share

Metrics

Record views

92

Files downloads

188