Under the background of the global integrated supply chain, the work of logistics is more and more complicated. Warehouse management is now an important part of logistics. The optimization of the logistics tracking system in the building material market proves that the tracking result of the system is highly reliable. The system has the advantages of small size, low cost, accurate positioning, real-time convergence, and high performance.

The optimization of transportation path for distribution vehicles, which is about the mixed tabu search method, can not only reduce the cost but also improve the optimization of the vehicle transportation path. This algorithm first studies the current situation of the logistics distribution vehicle transportation path and then uses the hybrid tabu search method to calculate the vehicle transportation path. According to the real case analysis, it can be proved that the hybrid tabu search calculation method can improve the efficiency, the proposed modern logistics distribution vehicle transportation path is also the best method, and the transportation cost is greatly reduced.

High-dimensional deep learning has been applied in all walks of life at present, among which the most representative one is the logistics path optimization combining multimedia with high-dimensional deep learning. Using multimedia logistics to explore and operate the best path can make the whole logistics industry get innovation and leap forward. How to use high-dimensional deep learning to conduct visual logistics operation management is an opportunity and a problem facing the whole logistics industry at present. The application of high-dimensional deep learning technology can help logistics enterprises improve their management level, realize intelligent decision-making, and enable accurate prediction. Starting from the total amount of logistics, regional layout, enterprise scale, and high-dimensional deep learning algorithm, this paper analyzes the current situation of China’s logistic development through multiweight analysis and explores the best path for multimedia logistics.