Effective Permutation Encoding for Evolutionary Optimization of the Electric Vehicle Routing Problem

Abstract

This paper addresses the problem of route planning for a fleet of electric vehicles departing from a depot and supplying customers with certain goods. This paper aims to present a permutation-based method of vehicle route coding adapted to the specificity of electric drive. The developed method integrated with an evolutionary algorithm allows for rapid generation of routes for multiple vehicles taking into account the necessity of supplying energy in available charging stations. The minimization of the route distance travelled by all vehicles was taken as a criterion. The performed testing indicated satisfactory computation speed. A real region with four charging stations and 33 customers was analysed. Different scenarios of demand were analysed, and factors affecting the results of the proposed calculation method were indicated. The limitations of the method were pointed out, mainly caused by assumptions that simplify the problem. In the future, it is planned for research and method development to include the lapse of time and for the set of factors influencing energy consumption by a moving vehicle to be extended.