Optimization of Logistics Distribution Network based on Ant Colony Optimization Neural Network Algorithm

Abstract

In order to improve the timeliness of logistics distribution, based on the theory of road network smoothness and reliability, the author conducted a study on the optimization of urban logistics distribution and transportation networks based on smoothness and reliability. The concept of logistics distribution and transportation network smoothness and reliability was proposed, and a logistics distribution and transportation network optimization model was established. The solving process of ant colony algorithm was given, and finally, a comparative analysis of a case was conducted. The results showed that: With a 6% increase in total delivery distance, the reliability of the delivery network has increased by 30%. This indicates that when using the model built by the author for distribution network optimization, effective optimization of network smoothness and reliability can be achieved, while only increasing the distance by a small amount. The optimal reliability of a smooth distribution network means that the probability of delivery delays is minimized, which is the most powerful guarantee for the effective accessibility of delivery. Verified the practicality of the constructed model. The proposed logistics distribution network optimization model has practical significance in guiding decision-making for optimizing urban logistics distribution transportation networks and reducing uncertainty in the process of urban logistics distribution.