A hybrid iterative local search algorithm for the electric fleet size and mix vehicle routing problem with time windows and recharging stations.

Abstract

As the cities around the world become larger, quality of life of the citizens is more and more threatened due to the traffic congestion, energy consumption, noise disturbance and carbon emissions because of of increasing transport. Electrical vehicles present an opportunity to reduce greenhouse gas emissions. But limited driving range and long recharging times are among the challenges that the research community has to face. This paper proposes an iterative local search algorithm coupled with a set partitioning model to solve The Electric Fleet Size and Mix Vehicle Routing Problem with Time Windows and Recharging Stations. Several types of electrical vehicles with varying driving range, capacity and fixed cost should service a set of customers within their time limits and during their tours each vehicle can be recharged in stations. We show the efficiency and the quality of our method by solving benchmark instances of the Heterogeneous Fleet Electric Vehicle Problems with Time Windows.