In my thesis I describe the production scheduling problem, which is known for every manufacturing company. To solve this, I implement a scheduling optimization software and bound it to an existing ERP system.
First of all, I show the hierarchical levels of enterprise production planning, especially the production scheduling during the operative planning process. In this context, I also present the most important goals and circumstances, which need to be kept in mind in a production environment.
In the next chapter, I expound all the important data bounded to production scheduling in the QAD EA ERP system. I explain the meaning and the database structure behind these data. I also present the data and functions of the on-PLAN production scheduling software, which provides a simple but powerful way for manual production scheduling based on the data of the QAD EA system.
After it, I describe the IBM ILOG CPLEX Optimization Studio, which is an integrated development environment, I use for solving the production scheduling problem. I show the relevant functions of the system in a complex example.
After I got familiar with the software, I create the mathematical model of a general production scheduling problem, and then I use it to create the solver model in the Optimization Studio.
Finally, based on the model I created in the chapter before, I implement a scheduling software in C#. This program is able to receive input data from different data sources, including the QAD EA ERP system, and create scheduling based on these data. I test the software on different sized datasets, including one from a production environment, and then I suggest some opportunities to develop the existing solution.