Applying Genetic Algorithms to the Optimization of Production Planning in a Real-World Manufacturing Environment

In this paper we present an optimization approach to a real-world production planning problem. Based on raw data that have been extracted from the Production, Planning and Control System of a company which produces special purpose vehicles and equipment, we have developed an architecture of an optimization system for production planning and scheduling in the manufacturing line of this company. The paper itself is divided into two major parts. The first part mainly deals with the theoretical background of production planning problems. In the second part of the paper we give an overview of the concrete scenario which is the subject of our research. Based on these fundamentals, we describe our approach to the problem, the modelling process and the architecture of the optimization system we plan to implement.