Electric Vehicles (EV) Route Optimization Using Artificial Hummingbird Algorithm

Selecting routes to Electric Vehicles (EVs) differ from regular vehicles. The proliferation of EVs requires an optimization algorithm to find the shortest and low-energy path to the destination. The physical network of EVs is modeled as a network of nodes with weighted edges. The area's topography, as well as the choice of battery, heavily influences the vehicle's power consumption; hence these parameters are also considered. The energy utilization of the electric vehicle is estimated to develop the shortest path-finding algorithm that finds the path with the cheapest edge. In this article, optimization is carried out with a metaheuristic algorithm with a bio-inspired design to provide the shortest route with the lowest energy use and the least travel time. The Artificial Hummingbird Algorithm (AHA) optimizes the route for electric vehicles, resulting in a solution that saves energy and trip time.