Combining Optimization Methods and Discrete Event Simulation: A Case Study in Flexible Manufacturing Systems

The studied problem is an extension of the well known job shop scheduling problem, in which the material handling system is considered as an overall part of the scheduling. This problem has many applications in flexible manufacturing systems. In these systems, jobs are transported from any machine to any other machine by automated guided vehicles. This problem has both an algorithmic and a structural complexity. We propose to take into account this double complexity by combining metaheuristic (for the optimization process), and discrete event simulation (for the evaluation of a solution). The results obtained show the efficiency of the presented approach, 11 new upper bounds are found on a benchmark of 40 instances of the literature. Realistic constraints like traffic congestion or collision could be included by a more sophisticated evaluation model