Investigation of Vehicle Logistics Cost Control Model Based on Internet of Things Mode Based on E-commerce Platform

Abstract

The rise of the Internet of Things and e-commerce platform has enabled logistics companies to embark on a fast-growing road. How to effectively control the cost of vehicle transportation under the condition of continuous increase in the total volume of logistics business is the key to influencing the sustainable development of logistics enterprises. Methods: In order to reduce the cost of vehicle transportation, the use of artificial intelligence ant colony algorithm to build intelligent deployment model is explored. Results:After analyzing the principle and implementation flow of the traditional ant colony algorithm, the ant colony algorithm is updated and optimized from the perspective of many dynamic factors and large changes in the logistics vehicle.Conclusion: A combination of optimal algorithm parameters is constructed to help logistics companies find the most cost-effective vehicle scheduling plan. Simulation tests show that the optimized ant colony algorithm can quickly find the optimal cost-effective route and effectively control the vehicle logistics costs.