Research On The Optimization Of Cargo Position Of Material Box Automated Stereoscopic Warehouse In D Company

The development of made in China 2025 and Industry 4.0 brings both opportunities and challenges to manufacturing.Logistics is an indispensable part of the manufacturing process,which plays a vital role in the overall operation of enterprises.As an important part of enterprise logistics,warehousing has been attached importance to by many researchers.The traditional storage mode can not meet the long-term survival requirements of modern enterprises.As a product of modern logistics,information technology and automation technology,automated stereoscopic warehouse has been widely used in modern enterprises.It can not only automatically extract goods,but also improve the efficiency of goods in and out storage.However,it also brings challenges to the distribution and management of goods,and the reasonable distribution of goods has become an urgent problem for enterprises.How to optimize the warehouse location,improve the storage efficiency and reduce the storage cost has become the focus of attention of manufacturing enterprises.This paper focuses on the optimization of cargo position of material box automated stereoscopic warehouse in D company.First of all,the paper expounds the research background and significance of the cargo position optimization problem in D Company,and explains the necessity of the research from the academic point of view,combining with the relevant literature and theoretical methods.Secondly,through the field investigation and the analysis of historical data of the company,combined with the status quo of material box automated stereoscopic warehouse,the existing problems are found.Thirdly,according to the actual situation of D Company and the target of cargo position optimization,the objective function optimization model is established in three aspects,namely,the efficiency of incoming and outgoing storage,shelf stability and material classification and storage.The idea of solving the problem is introduced according to the mathematical model and the multi-objective function solving method.Fourthly,a hybrid genetic simulated annealing algorithm is designed according to the solution idea.The algorithm is used to solve the model,and the optimization scheme is obtained.At the same time,the MATLAB software is used to simulate the distribution scheme before and after the optimization.Finally,compare the results before optimization with the results of genetic algorithm and genetic simulated annealing algorithm optimization,and the effectiveness of the optimization model and genetic simulated annealing algorithm is verified by combining thethree-dimensional simulation diagram of cargo position allocation.