Research On Dynamic Vehicle Route Optimization Of Cold Chain Logistics Distribution Based On Internet Of Things

With the development of our country's society and economy,the development of cold chain logistics is promoted rapidly by the diversification and individualization of consumers' demand for fresh agricultural products.At the same time,it also puts forward higher requirements for cold chain logistics.However,the current development of cold chain logistics is still at the initial stage in our country,there are still some problems such as unreasonable cold chain logistics distribution planning,high logistics costs and unsatisfactory customer satisfaction etc.Cold chain logistics distribution is a key link in the entire cold chain logistics activities.In meeting the dynamic needs of customers,how to combine the Internet of Things technology and Multi-Temperature Joint Delivery to optimize the cold chain logistics distribution vehicle path,thereby improving customers satisfaction and reduction of cold chain logistics costs are the key to current research.This article first reviewes the current research status of cold chain logistics distribution,Internet of Things-based distributive logistics and Multi-Temperature Joint Delivery at home and abroad,and points out the deficiencies of current research.It discusses the related theories of cold chain logistics,cold chain logistics Vehicle Routing Problem,Internet of Things technology,and Multi-Temperature Joint Delivery.And clarifies the characteristics of cold chain logistics,the classification of cold chain logistics Vehicle Routing Problems,the three-tier construction of the Internet of Things and related the key technology and the Multi-Temperature Joint Delivery method,and analyzes the feasibility and advantages of combining the Internet of Things and Multi-Temperature Joint Delivery to optimize the path of cold chain logistics distribution vehicles.Secondly,constructs the objective function with the smallest distribution cost,analyzs various costs in the entire distribution link,including fixed costs,cold storage costs,vehicle driving costs,time window penalty costs,cargo damage costs and the cost of using Io T technology,and puts forward a strategy to solve the dynamic needs of customers.By comparing the scope of application of various algorithms in modern heuristic algorithms,selecting Artificial Fish Swarm Algorithm to solve dynamic problems,analyzing the limitations of the basic Artificial Fish Swarm Algorithm,then the basic Artificial Fish Swarm Algorithm is improved,and the improved Artificial Fish Swarm Algorithm is verified by example to prove that the improved algorithm is more efficient and accurate.Finally,the built model is applied in actual distribution,the improved Artificial Fish Swarm Algorithm is used to find the optimal distribution route,and the vehicle load and other factors under static and dynamic customer demand are compared to prove the validity of the research.The cold chain logistics distribution vehicle path model and improved Artificial Fish Swarm Algorithm established in this thesis can be applied to the actual cold chain logistics distribution path formulation work,and it also has certain reference significance for other similar cold chain distribution.