Optimal Path Selection for Multi-weight Logistics Combined With High-dimensional Deep Learning Algorithms

Abstract

The optimal path selection technology of multi-weight logistics combined with
high-dimensional deep learning algorithms can effectively solve the cost problems that
lead to the cumbersome delivery process. Other solutions to the logistics path (such as
management) cannot effectively solve this problem. The successful development of the
optimal path selection of multi-weight logistics extends the distribution path to each city,
uses high-dimensional deep learning algorithms to establish models, determines the
optimal path of multi-weight logistics, and achieves cost control.