Multiple fidelity simulation optimization of hospital performance under high consequence event scenarios

Authors:
Jason R Schenk;Deng Huang;Ning Zheng;Theodore T. Allen
Affiliations:
The Ohio State University, Columbus, Ohio;Scientific Forming Technologies Corporation, Columbus, Ohio;The Ohio State University, Columbus, Ohio;The Ohio State University, Columbus, Ohio
Venue:
WSC '05 Proceedings of the 37th conference on Winter simulation
Year:
2005

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Abstract

In optimizing systems, experimental models are often available with different levels of cost and different levels of "fidelity" 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.