Simulation-based optimization in make-to-order production: Scheduling for a special-purpose glass manufacturer

We consider the problem of determining schedules for make-to-order production of companies that manufacture special purpose glasses. Due to sensitive raw materials and high quality specifications, scheduling is affected by disturbances arising from stochastic processing times and stochastic scrap rates. Scarce machine capacities, limited availability of transportation equipment, and technical or organizational temporal constraints lead to a complex planning problem. Hence, discrete-event simulation is valuable for analyzing the impact and robustness of alternative schedules, but it fails in efficiently guiding the search for optimal control parameters. In order to overcome this drawback, we propose a simulation-based optimization approach that relies on coupling simulation and optimization through a relaxation-based schedule generation procedure. Schedules are generated employing a mixed-integer programming model for which input parameters and additional constraints are iteratively derived using a simulation model. We evaluate our approach considering real-world instances and present preliminary computational results indicating its effectiveness.