Algorithmic Research on Vehicle Path Problem in Logistics Distribution

Due to the rapid development of the modern e-commerce industry and the increasingly fierce competition in the logistics and distribution industry, vehicle routing problems play a crucial role in logistics and distribution. Adopting scientific and effective algorithms to select appropriate vehicle transportation paths can reduce logistics costs, improve delivery efficiency, and improve customer satisfaction and service quality. As a result, this paper proposes to use Hopfield neural network algorithm to solve the small-scale single-vehicle path problem, and use MATLAB to conduct simulation experiments to verify the effectiveness of the algorithm; for the large-scale multi-vehicle path problem, this paper embeds k-means clustering and its correction process into Hopfield neural network, and adopts the divide-and-conquer approach of clustering and then searching for optimization to solve the problem, and Simulation experiments are carried out for this problem.