This work presents a mixed integer linear programming (MILP) formulation to find an optimal solution to a small instance of the complex
scheduling problem in a make-to-order production. Minimizing the make span, the MILP generates the optimal schedule for the autonomous
guided vehicles (AGVs) in a blocking reentrant job shop environment with different jobs. Feasible schedules for the machines and the AGVs
are generated from different sized instances to evaluate the limits of the mathematical model. These results are compared to a priority rule
based dispatching system, evaluated with an discrete event simulation. The comparison leads to the insight, that on the one hand optimal
solutions cannot be calculated for most real world scenarios due to the complexity and on the other hand the application of a standard
dispatching rule lead to poor performances neither of the technics are satisfying the need to generate an appropriate schedule. As a result
possible solutions are presented.