An online intelligent vehicle routing and scheduling approach for B2C e-commerce urban logistics distribution

Abstract This paper investigates a large-scale vehicle routing and scheduling problem of B2C e-commerce urban logistics distribution in China. A qualitative and quantitative combined online intelligent scheduling approach is developed by means of incorporating operations research methods and artificial intelligence technologies. This approach aims to make good use of advantages of qualitative and quantitative methods by the complementarity of model-based computing in operations research and knowledge-based searching in artificial intelligence. A case study from a Chinese e-commerce company demonstrates its effectiveness.