Comparative Analysis of Metaheuristic Techniques to Solve Electric Delivery Vehicle Routing Problems

The emergence of electric vehicles has brought along fresh challenges for streamlining delivery routes that factor in diverse variables, like travel time, distance, and energy usage, to determine the delivery costs. In this regard, a comprehensive problem formulation is proposed in this paper that considers all these parameters concurrently to determine more sustainable and cost-effective delivery routes. This study compares the efficacy of four meta-heuristic algorithms - ACO, PSO, GA, and CS - to optimize the electric delivery vehicle routing problem. The results show that ACO outperforms other algorithms for various scenarios. This research bears significant implications for enhancing the efficiency and sustainability of electric vehicle delivery systems in practical scenarios.