Research On The Optimization Of Pharmaceutical Cold Chain Logistics Distribution Pat

In recent years,China has continuously updated its pharmaceutical cold chain logistics policy,which has created a good market environment for China’s pharmaceutical cold chain logistics industry.The outbreak of the COVID-19 and the aggravation of the aging phenomenon have also driven people’s demand for drugs,and people’s focus has shifted from the production quality of drugs to the whole transportation of pharmaceutical circulation.On the one hand,the development of pharmaceutical cold chain logistics still has the problems of imperfect structure system,backward technology and unsound standards and norms,which not only lead to the high cost of pharmaceutical cold chain logistics,but also cannot guarantee the safety of drugs.On the other hand,the low utilization rate of vehicles and unreasonable distribution routes restrict the development of pharmaceutical cold chain logistics in China.Based on the above background,the research on the distribution route of pharmaceutical cold chain logistics and the development of a reasonable and efficient distribution plan are essential to enhance the core competitiveness of enterprises and customer satisfaction.This article summarizes the vehicle routing problem and pharmaceutical cold chain logistics based on existing literature,and based on the relevant theories of vehicle routing problem,considering that logistics enterprises may use different vehicle models for task delivery and the time-varying vehicle speed during the delivery process,analyzes and studies the optimization problem of multi vehicle pharmaceutical cold chain logistics delivery paths under time-varying road networks.Firstly,based on the actual delivery situation,a speed time segmented function was established using the Baidu Map transportation big data platform to describe the time-varying road network.By analyzing and defining the specific calculation of vehicle travel time,the calculation method of various costs in the vehicle delivery process was clarified,and a pharmaceutical cold chain logistics delivery model was constructed with the optimization goal of minimizing the comprehensive logistics cost.Then,by analyzing and comparing the advantages and disadvantages of commonly used solution methods,the sparrow search algorithm was selected as the solution method for this article.Based on the characteristics of the problem,the sparrow search algorithm was improved,retaining the basic search behavior of the sparrow search algorithm.Drawing on the cross strategy of neighborhood search strategy and genetic algorithm,the position update methods of discoverers,followers,and vigilantes were redefined,and 2-opt and self-adaptation strategies were introduced to improve the local development ability of the algorithm.Using the method of half random and half reverse mutation to obtain the initial population to improve the diversity of the algorithm population.Finally,the effectiveness of the improved algorithm and problem optimization model was verified through TSP international examples and practical cases.The results show that by comparing the performance of the two algorithms in TSP international and actual cases,it can be seen that the improved strategy designed in this paper effectively improves the robustness and optimization performance of the algorithm.Compared with the traditional sparrow search algorithm,using the improved sparrow search algorithm not only shortens the driving distance,but also improves the effective loading rate of vehicles and reduces the overall delivery cost,thus proving the effectiveness of the algorithm.In addition,by analyzing the operation results of the improved sparrow search algorithm under two speed states,the increase in delivery costs under time-varying road networks balanced the impact of road congestion on the delivery process,verifying the effectiveness of the mathematical model.Finally,a distribution plan was developed for the enterprise,providing theoretical reference and guidance for decision-making,and enriching relevant research on vehicle routing problems.