Dynamic specialization for symbiotic simulation-based operational decision support using the evolutionary computing modelling language (ECML)

Abstract

Simulation-based what-if analysis is an important tool that can be used to support operational decision making. Solutions to operational decision problems have to be found in a limited period of time. As a result of these time constraints, not all candidate solutions can be evaluated by means of simulation. Essentially, this problem solving process is an optimization process. Specialization of the optimization method can help to reduce the computing budget needed to find an appropriate solution. However, since operational conditions are constantly changing, the exact problem is not known at design time. Therefore, the optimization method has to be specialized during runtime. This can be done by dynamically incorporating situation-dependent problem-specific knowledge into the optimization process. We introduce a method based on an evolutionary algorithm, which supports dynamic specialization. Furthermore, we demonstrate the effectiveness of this method in the context of a semiconductor manufacturing application.

Keywords:

• decision support
• symbiotic simulation
• evolutionary computing

Notes

1 Note that here we assume that there is only one simulation model available, which is appropriate for the purpose of the what-if analysis. It is thus not necessary to explicitly specify the model as part of the what-if scenario.