Research On The Intelligent Warehouse Management System

With the development of modern logistics, Supply chain management, factory automation and management information system under the environment of Computer Information Manufacturing provide more and more requirements on Warehouse Management System. Corporations not only be satisfied with the exact stock information, but also be more interested in how to quicken the goods' speed of order-picking and in or out storage through optimize scheduler, improve the efficiency and reduce the error by barcode and so on. These science and technology are regarded more and more important.The author engaged in the project of one ship materials warehouse as a graduate student. After the research on the order-picking problem of the fixed shelve and the optimize problem of in or out storage path, author designed the intelligent warehouse management system. Firstly, the requirement model and object model of the intelligent warehouse management system are established based on Unified Modeling Language and database is founded; Then, a kind of rapid hybrid genetic algorithm is analyzed and designed according to the requirements of the order-picking problem of the fixed shelve and the optimize problem of in or out storage path, its efficiency is validated by the simulation; Finally, the software is explored and then used.The main study works of this dissertation are as follows:(1) Firstly, we analyse the requirements of the intelligent warehouse management system detailedly. The model of the system is established using Unified Modeling Language and object-oriented method. In the process, we build the requirement model by use case diagram and activity diagram, build the object model by class diagram and sequence diagram. On the foundation of modeling, we design the database in detail, and connection table and field table.(2) Secondly, According to the requirements of the order-picking problem of the fixed shelve, a kind of rapid and efficient hybrid genetic algorithm is analyzed and designed. A compensatory algorithm is presented for the construction of the initial population and a cross arithmetic operators and converse mutation arithmetic operators enlightened by greedy algorithm are for the operation. Then, considering the structure of shelf, with the view of order-picking best times, we sum up the mathematical model of the order-picking problem of fixed shelve and solve it by the hybrid genetic algorithm. The simulation indicates that this method can acquire good results, satisfying the demands of the work as to efficiency and optimization results. The algorithm is simply and effective.(3) Thirdly, we study the application of the hybrid genetic algorithm in the in or out storage path optimize problem. With the view of the shortest time, the model of the in or out storage path optimize problem is build through the analysis of warehouse shelve frame. Then, the hybrid genetic algorithm is used to solve the problem, and to help the design of the warehouse management system. So, this enhances the efficiency of the in or out and decrease the error.(4) Fouthly, on the basis of the above work, we design and debug the software. The software is being used now. In practice, the system enhances the whole efficiency of in and out and lowered the errors consumedly.Finally, we hope that the work and study in this dissertation can improve the intelligent and automation degree of the warehouse and impulse the storage development of our country.