Leveraging Emerging Technologies for Green Vehicle Routing Problem Optimization

The main aim of Green Vehicle Routing Problem (G- VRP) is to find optimal routing scheme while reducing environmental emissions and energy consumption. However, conventional optimization approaches often fail to address the complexity of G- VRP, especially in urban areas, due to limitations in scalability and adaptability. This paper reviews the latest developments in emerging technology to address these challenges. In particular, a combination of machine learning models, genetic algorithms and Internet of Vehicles (10 V) systems have been used to improve G- VRP performance. Machine learning models are used to predict energy consumption and traffic patterns; genetic algorithms create optimized routes that reduce both operating costs and environmental footprint. 10 V technologies facilitate real-time communication between vehicles and infrastructure, enabling dynamic route adjustments in response to traffic disruptions or environmental characteristics. This paper analyzes literature to identify the contribution of new technologies to developing a Green VRP, with a view to inspiring future research to develop efficient, smart and sustainable G- VRP systems.