Research And Development Of ERP And Flexible Job Shop Scheduling System Based On Genetic Algorithm

Entering the21st century, the economy in our country develops very fast, and thecomprehensive national power of our country improves significantly. And as a result, themanufacturing industry also has a great-leap-forward development. Now China is on theway to become the World’s manufacturing powerhouse, and is struggling for the goal ofbecoming the world’s manufacturing center. However, our manufacturing enterpriseshave not realized the significance of the ERP System, and the level of the ERPapplications is low and unbalance. This greatly restricted the development of China’smanufacturing industry.From macroscopic view, we need to work out a program of MPS, MRP and CRP.From microcosmic view, we need to carry out the Job shop scheduling to machine fast.The classic JSP is out of touch, and can not be applied to actual production. The flexiblejob-shop scheduling problem (FJSP) is a further development of classic job shopscheduling. It is more practical production, and has a certain practical significance.In this paper, we are to design an ERP and Flexible Job Shop Scheduling System. Inthe research, we use ASP.NET as the development environment, use Visual Studio2008and MATLAB R2008a as development tool, use C#as programming language, useMicrosoft SQL Server2005as database, use improved GA as scheduling algorithm, anddevelop the ERP and Flexible Job Shop Scheduling System. This system is based onactual demand of the enterprises, and uses the fundamental data of the business planning.Firstly it formulates the MPS, MRP and CRP plans. And secondly we go on the FJSP.And in the application of intelligent scheduling process optimization algorithms-improved genetic algorithm, so that the workshop resource utilization is maximized.In summary, the Research and Development of ERP and Flexible Job ShopScheduling System are an attempt to let ERP and FJSP work together. It has certainpractical significance on how to plan for manufacturing enterprises to generate andproduction scheduling.