Research On Dynamic Planning Of Tobacco Logistics Distribution Path Of Company A Based On Real Time Information

The distribution of tobacco products is the core business in the tobacco industry and the key way for tobacco enterprises to reduce costs and increase efficiency.Under the new situation of the vigorous development of modern logistics industry in this century,the reasonable planning of tobacco product distribution is the basis for the realization of "cigarette top level" and the fuel for the rapid development of the tobacco industry.The optimization of distribution logistics of tobacco enterprises has become a key problem to be solved urgently in the tobacco industry.A Tobacco Company is responsible for the city’s tobacco monopoly law enforcement,cigarette production and operation,and tobacco leaf production and operation.The company has 3428 distribution outlets,a large number of tobacco products are distributed,and the distribution outlets are scattered,while the product distribution path is still the traditional way as its main distribution method.Therefore,the distribution cost is too high and resources are wasted.Therefore,it is of great significance to study and optimize the distribution path of Company A in order to reduce its operating costs and improve its distribution efficiency.This paper will take A Tobacco Company as an example to analyze the logistics operation process and actual business needs of A Company,and divide the problem into two parts: distribution area division and vehicle path planning within the area.Establish relevant path information database,obtain real-time information such as road situation and weather conditions,build distribution cost mathematical model and carry out optimization analysis,and finally solve the problem by parallel calculation,so as to improve the rationalization level of distribution process.The main contents are as follows:(1)Based on the clustering algorithm,aiming at the unreasonable distribution area division of A Tobacco Company,the distribution area is re-divided by taking into account the actual location of the distribution demand point,the maximum load of vehicles and other information.By considering the actual influencing factors of the problem and comparing K-Means,K-Medios and other clustering algorithms,K-Medios clustering algorithm is finally used.The evaluation criteria function,similarity,K value and initial center point are calculated,and the clustering results are obtained.The sub-regions meet the single vehicle distribution conditions.(2)Genetic algorithm is applied to optimize the single vehicle path in a fixed area.Select the representative sub-regions in the total operation area of A Tobacco Company,and consider the road uncertainty,customer demand point location,actual road network and other information to build the TSP mathematical model.Sort out the data to specify the quantity in the model,and apply genetic algorithm to optimize the path of vehicles in the region to get the optimized path.Compare the path cost and customer satisfaction before and after optimization to verify the effectiveness of optimization.Through the analysis and optimization of the distribution path problem of Company A based on real-time information,it provides a more reasonable solution for the practical application of Company A’s improvement work,and also provides a new solution for the solution of similar problems.