USE OF A CLASSIFIER IN A KNOWLEDGE-BASED SIMULATION OPTIMIZATION SYSTEM

This article defines and develops a simulation optimization system bas ed upon response surface classification and the integration of multipl e search strategies. Response surfaces are classified according to cha racteristics that indicate which search technique will be most success ful. Typical surface characteristics include statistical measures and topological features, while search techniques encompass response surfa ce methodology, simulated annealing, random search, etc. The classify- then-search process flow and a knowledge-based architecture are develo ped and then demonstrated with a detailed computer example. The system is useful not only as an approach to optimizing simulations, but also as a means for integrating search techniques and thereby providing th e user with the most promising path toward an optimal solution. (C) 19 95 John Wiley & Sons, Inc.