TY - JOUR

T1 - Optimal charging and repositioning of electric vehicles in a free-floating carsharing system

AU - Folkestad, Carl Axel

AU - Hansen, Nora

AU - Fagerholt, Kjetil

AU - Andersson, Henrik

AU - Pantuso, Giovanni

PY - 2020

Y1 - 2020

N2 - Carsharing has received increased attention from the Operations Research community in recent years. Currently, many systems are adopting electric vehicles that require charging when battery levels fall below a given level. To do this, staff is often used to move cars to charging stations. Repositioning cars, rather than simply moving them to the closest charging station, might provide a better distribution of cars and in turn generate increased revenue and customer service while only marginally increase the operational costs. We present a mathematical model for the problem of charging and repositioning a fleet of shared electric cars. The model considers the assignment of cars to charging stations and the routing of staff and service vehicles. The complexity of the resulting mixed integer program makes it impossible to solve real world instances using a commercial solver. Therefore, we propose a new Hybrid Genetic Search with Adaptive Diversity Control algorithm. Tests based on data from a real life carsharing organization demonstrate that the proposed method can handle real size instances and that combining repositioning and charging operations can give significant benefits.

AB - Carsharing has received increased attention from the Operations Research community in recent years. Currently, many systems are adopting electric vehicles that require charging when battery levels fall below a given level. To do this, staff is often used to move cars to charging stations. Repositioning cars, rather than simply moving them to the closest charging station, might provide a better distribution of cars and in turn generate increased revenue and customer service while only marginally increase the operational costs. We present a mathematical model for the problem of charging and repositioning a fleet of shared electric cars. The model considers the assignment of cars to charging stations and the routing of staff and service vehicles. The complexity of the resulting mixed integer program makes it impossible to solve real world instances using a commercial solver. Therefore, we propose a new Hybrid Genetic Search with Adaptive Diversity Control algorithm. Tests based on data from a real life carsharing organization demonstrate that the proposed method can handle real size instances and that combining repositioning and charging operations can give significant benefits.

KW - Free-floating carsharing

KW - Genetic algorithm

KW - Integer programming

KW - One-way carsharing

KW - Vehicle relocation optimization

UR - http://www.scopus.com/inward/record.url?scp=85071638671&partnerID=8YFLogxK

U2 - 10.1016/j.cor.2019.104771

DO - 10.1016/j.cor.2019.104771

M3 - Journal article

AN - SCOPUS:85071638671

VL - 113

JO - Computers & Operations Research

JF - Computers & Operations Research

SN - 0305-0548

M1 - 104771

ER -