Empirical model-building and response surface
Empirical model-building and response surface
Convergence properties of ordinal comparison in the simulation of discrete event dynamic systems
Journal of Optimization Theory and Applications
Rates of convergence of ordinal comparison for dependent discrete event dynamic systems
Journal of Optimization Theory and Applications
Response Surface Methodology: Process and Product in Optimization Using Designed Experiments
Response Surface Methodology: Process and Product in Optimization Using Designed Experiments
Simulation optimization using metamodels
Winter Simulation Conference
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Traditionally, Response Surface Methodology (RSM) is cardinal in nature. Ordinal optimization was only introduced recently. Since ordinal optimization has been proven to be successful in certain applications, this paper aims to investigate whether ordinal optimization improves RSM by developing ordinal RSM and comparing it with cardinal RSM in terms of efficiency, accuracy and consistency. Assuming that the performances of systems can be expressed as functions of their parameters, both ordinal and cardinal RSM are simulated for several simple multivariable mathematical functions and the effectiveness of ordinal RSM evaluated. It was found that ordinal does not always improve RSM, especially in functions which exhibit a large gradient change over a small region.