Application of a memetic algorithm to the fleet size and mix vehicle routing problem with electric modular vehicles
Authors
D. Rezgui, J. Chaouachi-Siala, W. Aggoune-Mtalaa, H. Bouziri
Reference
in Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO 2017), Berlin, Germany, 15-19 July, ISBN: 978-145034939-0, vol. 2017-January, pp. 301-302, 2017
Description
Electric vehicles have emerged as a new promising technology guaranteeing sustainable transport activities. To save the environment and avoid our dependence on foreign oil, new laws and regulations concerning the emission of greenhouse gases are made in order to reduce harmful emissions and promote electric vehicles for urban goods distribution. .is paper proposes to address the electric Modular Fleet Size and Mix Vehicle Routing Problem with Time Windows, which incorporates electric modules that can be recharged at customer locations. For that purpose, we apply a memetic algorithm that combines a Genetic Algorithm with a Local Search method. Experimental results demonstrate that with the modularity feature, using electric vehicles for freight delivery in cities is interesting economically.
