Contactless Distribution Path Optimization Based on Improved Ant Colony Algorithm

In the context of the normalization of the epidemic, contactless delivery is becoming one of the most concerned research areas. In the severe epidemic environment, due to the frequent encounter of bayonet temperature measurement, road closure, and other factors, the real-time change frequency of each traffic information is high. In order to improve the efficiency of contactless distribution and enhance user satisfaction, this paper proposes a contactless distribution path optimization algorithm based on improved ant colony algorithm. First of all, the possible traffic factors in the epidemic environment were analyzed, and the cost of each link in the distribution process was modeled. Then, the customer satisfaction is analyzed according to the customer service time window and transformed into a cost model. Finally, the total delivery cost and user satisfaction cost were taken as the optimization objectives, and a new pheromone updating method was adopted and the traditional ant colony algorithm was improved. In the experiment, the effectiveness of the proposed model and algorithm is verified through the simulation optimization and comparative analysis of an example.

Automated summary

In the context of normalization of the epidemic, contactless delivery has become a major research area. This paper proposes a contactless distribution path optimization algorithm based on an improved ant colony algorithm, which analyzes traffic factors and customer satisfaction in the epidemic environment, and improves efficiency and user satisfaction. Through simulation optimization and comparative analysis, the effectiveness of the proposed model and algorithm is verified.