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
SN - 0305-0548
VL - 113
JO - Computers & Operations Research
JF - Computers & Operations Research
M1 - 104771
ER -