Comparative Optimization of Electric Vehicle Routes Using Graph Algorithms and Mathematical Programming

This work proposes a comparative approach to the routing problem of electric vehicles (EVs), using three methods: the A* algorithm, the Dijkstra algorithm and a mixed integer programming (MIP) model. Routes are evaluated in nine cost scenarios that combine travel time, recharge time and distance, with different weightings. The input data is obtained from OpenChargeMap and modeled as a directed graph, where the edges represent feasible displacements based on the vehicle's range. Experimental results show that Dijkstra and MIP consistently identify optimal routes in all scenarios, while A* can fail in multi-criteria configurations. Dijkstra had faster computational performance than MIP, making it suitable for real-time applications. The results are presented in tables and maps, highlighting the differences in cost and route profiles between the methods.