Abstract
In this study, the tour planning problem for electric vehicles is investigated. We aim to derive the optimal route and thus, to maximize profitability and minimize range anxiety within the time horizon. To solve this problem, a bi-objective mixed integer model is proposed. Specifically, we first introduced the reliability of route planning and quantified it as a cost with specific functions. The nonlinear model was then converted into a bi-objective mixed integer linear program, and an interactive branch and bound algorithm was adopted. Numerical experiments conducted on different networks have shown that the model that considers range anxiety offers more effective solutions. This means that our model is able to plan the routes with high reliability and low risk of profit loss and accidents.
Highlights
About 86% of global primary energy demand depends on fossil fuels, in which coal, gas and oil account for 23%, 27% and 36%, respectively
This study aims to derive the optimal route for the electric vehicle tour planning (EVTP) problem so that profitability is maximized and range anxiety is minimized within the time horizon
We conduct numerical experiments on two sets of benchmark networks derived from well-known instances in previous literature and show the model considering range anxiety is able to plan the routes with high reliability and low risk of profit loss and accidents
Summary
About 86% of global primary energy demand depends on fossil fuels, in which coal, gas and oil account for 23%, 27% and 36%, respectively. Wang et al [8] describe RA as the mental distress, or fear, of being stranded on roads should the battery run out They imply that even if a completed charging network exists, EV drivers could still suffer from RA. This study aims to derive the optimal route for the electric vehicle tour planning (EVTP) problem so that profitability is maximized and range anxiety is minimized within the time horizon. We first define the reliability of an electric vehicle tour plan with range anxiety and propose a function form to quantify it. 4. We conduct numerical experiments on two sets of benchmark networks derived from well-known instances in previous literature and show the model considering range anxiety is able to plan the routes with high reliability and low risk of profit loss and accidents.
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