Towards adaptive simulation-based optimization to select individual dispatching rules for production control

Due to the increasing complexity of contemporary production scheduling problems, it is generally not possible to calculate nearly optimal production schedules in an acceptable amount of time. Hence, normally, dispatching rules are used to determine the job sequences. However, the selection of suitable dispatching rules is not a trivial task and depends on the relevant key performance indicators. Moreover, the suitability of dispatching rules changes over time because of the stochastic and dynamic nature of manufacturing systems. This paper proposes an adaptive simulation-based optimization approach to select individual dispatching rules for production control. The paper's contribution is two-fold. First, it shows that the proposed approach improves the performance compared to benchmark approaches in a manufacturing scenario from semiconductor industry. Second, in order to be able to react quickly to dynamic changes, it proposes strategies for maintaining information from previously calculated solutions after a change, such as a machine breakdown, occurred.