Research On Functional Partitioning And Slotting Optimization Of Auto Parts Warehouse In Q Enterprise

The rapid development of China’s economy has led to the rapid development of the automobile industry.With the increase of production lines and the diversification of models in the automobile industry,there are more and more types and quantities of automobile parts,which brings serious challenges to China’s automobile logistics work.Because the auto parts industry involves many kinds of parts,requires high precision and is more complex than other industries,it has gradually become the focus of enterprise cost control.The optimization of storage system has a significant effect on planning and design of logistics system.In the warehousing process,the material retention time is the longest,and a lot of storage costs are brought.Therefore,it is imperative to plan and optimize the warehouse reasonably.According to the actual operation problems of warehouse A and B in the parts warehouse area of Q Automobile Enterprise,this paper proposes a strategy of combining two warehouses to improve the utilization rate of warehouse storage.Taking its storage status as an actual case,it classifies materials according to their nature,and on this basis,it optimizes the allocation of goods in the ground storage area and the high shelf area,so as to solve the problem of high cost caused by the simultaneous operation of two warehouses in Q Automobile Enterprise,and low storage utilization rate caused by a large number of materials stacked on the ground Low delivery efficiency caused by random storage of materials.The main research contents of this paper are as follows:.The first part mainly realizes the function partition optimization.For the high operation cost of two warehouses,the strategy of combining two warehouses into one is proposed to solve the problem;The warehouse function zoning optimization is carried out to achieve the overall goal of reducing the ground pile,increasing the overhead,and accommodating the two warehouses of materials;Consider the lowest cost of new overhead equipment.First of all,the inventory forecast method is used to forecast the inventory of materials;The materials are classified as a whole according to the predicted inventory,and the materials in the ground storage area and elevated area are divided according to the size and other properties;The functional zoning is modeled according to the material classification zoning results.With the minimum number of new shelf equipment as the goal,the hierarchical sequence method is used to solve the multi-objective function step by step,and the zoning results are solved by Lingo.The second part mainly realizes the optimization of cargo space in the ground storage area and elevated area.First of all,the storage location optimization model is established for the ground storage area with the goal of outbound efficiency,and the storage location optimization is carried out for the two areas of the ground storage area respectively,and the storage location coordinates of the two areas of the ground storage area are solved with Lingo;Secondly,Apriori algorithm is used to calculate the correlation degree of materials in the elevated area.According to the correlation degree,the materials are classified into several categories.On this basis,a mathematical model is established with the objectives of delivery efficiency,material correlation and shelf stability.Ant colony algorithm is used to solve the results of the location allocation,and the results are analyzed.This paper finally realizes the optimization of warehouse partition.By increasing the number of shelf equipment and reducing the number of ground stacks,it greatly improves the storage capacity and delivery efficiency of the warehouse.The optimization of storage location makes the material storage orderly,reduces warehouse cost position and improves efficiency.At the same time,this paper has great research value and practical significance for the research of material warehouse functional zoning and location allocation,and provides a valuable decision-making reference for the optimization of warehouse area and reasonable location allocation of auto parts enterprises.