Integrated production and staff planning for heterogeneous, parallel assembly lines: an application in the automotive industry

We consider an integrated production and staff planning problem that occurs in the automotive industry. In particular, we focus on a production environment with heterogeneous, parallel assembly lines and search for a least cost schedule for producing a forecasted demand taking into account the application of volume flexibility instruments. The problem is modelled as a (non-linear) mixed-integer programme and solved by using dynamic programming. We present two case studies that are derived from real-world data in order to show the practical usability of our method. Compared to previous approaches presented in the literature, our dynamic programming method can achieve cost improvements of more than 10%.