Multiple fidelity simulation optimization of hospital performance under high consequence event scenarios
Jason R. Schenk, Deng Yang Huang, Ning Zheng, Theodore T. Allen · Winter Simulation Conference · 2005
In optimizing systems, experimental models are often available with different levels of cost and different levels of or trustworthiness, a fact that can be exploited. For example, a highly detailed model might be made for a few possible configurations, supplemented by a large number of rough models that are less expensive to construct. The purpose of this paper is to illustrate the application of a recently proposed multiple fidelity sequential kriging optimization (MFSKO) method to derive the optimal resource allocation for disaster preparedness of a hospital. The system is evaluated via discrete event simulations of two sophistication levels. The MFSKO method integrates multiple fidelity data, including real-world data, in search for the global optima with less total evaluation cost. Kriging meta-models are generated as by-products of the optimization.