Research On Joint Optimization Of Production And Distribution Decision Considering Downstream Inventory Information

The optimization of production and distribution has always been a hot topic in the field of operations research and logistics optimization.It involves not only management science and engineering,but also computer applications.At present,the academic community has carried out research on production and distribution issues of various types of materials,such as fresh food,emergency supplies,fast-moving consumer goods,etc.,but the academic papers related to the production-distribution research of power materials in the database are not so extensive.Moreover,in recent years,with the continuous expansion of market demand,the demand for measuring instruments in various regions has also expanded year by year,and the production-distribution problem of measuring instruments has become increasingly exposed and needs to be solved urgently.Therefore,this paper takes the State-owned Z Power Company as the background and relies on the power materials of all cities(counties)in Z Province to study and discuss the production-distribution decision-making of measuring instruments.Firstly,this paper studies the joint optimization problem of production-distribution decision in two-stage supply chain environment.In this paper,the basic model considering distribution priority and the extended model considering carpooling problem are given.The extended model is considering the model of delivery priority.Carpool constraints and route constraints have been added.This paper formulates production decision and distribution decision from the perspective of upstream and downstream integration optimization,optimizes the upstream production quantity and the distribution quantity of downstream wholesalers by using demand forecasting and actual inventory information,and improves the truck full load rate through the strategy of carpooling between the two places,and then obtains A more optimized operating plan.Then,the paper writes the code through Lingo software,and carries out an example calculation on the model considering the delivery priority and the model considering the carpooling problem to verify the validity of the model.The calculations show that the model considering the delivery priority has played a role in cost reduction and efficiency enhancement.The model expansion considering the carpool problem is more effective in reducing the distribution cost.Then,we conducted a sensitivity analysis on the more optimized model expansion,and studied the influence of different parameter changes on the selection of production-distribution strategy and system cost.The main parameters are downstream customer scale,capacity limitation,and vehicle.Factors such as capacity and conversion factor.The study found that customer size has the greatest impact on the calculation results of the model,followed by the maximum capacity limit of the upstream plant,the customer's onboard capacity,and the conversion factor has the worst impact on cost.Finally,in order to make the model better cope with the internal and external uncertainty,this paper establishes a robust optimization model based on the distribution priority model.The same model and parameter analysis are also carried out using Lingo to prove the model.Robustness and robustness of the solution.