Bat Optimization Model for Electric Vehicle Route Optimization Under Time-of-Use Electricity Pricing

Abstract

In the framework of fuel reduction and energy conservation, the electric vehicles (EV’s) has been identified as a promising option in contrast to fuel-driven vehicles. EV’s battery limits to require visiting a greater number of times to the recharging stations, which must be viewed as in the route planning to keep away from inefficient vehicle routes with lengthy diversions. These problems have to consider, we propose an Efficient Electric Vehicle Route Optimization with Time-of-Use Electricity Pricing using Bat algorithm. Which can reduce the used vehicles as well as electricity-cost and total travel distance. Additionally, functional model and collective models are used to minimize the objectives: distance and cost. The computational assessment in light of the notable benchmarking test instances exhibits, proposed optimization algorithm electricity cost conservation on average 12.17% with Learnable Partheno-Genetic Algorithm (Yang et al. in IEEE Trans Smart Grid 6:657–666, 2015) 8.45% with VNS/TS Algorithm (Lin et al. in Trans Res Part-C 130:103285, 2021) and 5.15% with Mixed Integer Programming model (Ham and Park in IEEE Access 9:37220–37228, 2021). © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.