A pseudo-random number assignment strategy for the estimation of quadratic metamodels

Whereas an optimal Pseudo-Random Number (PRN) assignment strategy for simulation experiments involving the estimation of linear metamodels currently exists, no such optimal assignment strategy for quadratic metamodels has been proposed. This situation is now rectified by the introduction of a PRN assignment strategy for a quadratic metamodel for 3 k factorial designs. In addition to extending the theory from linear to quadratic metamodels, the proposed PRN strategy is shown to be superior to a number of existing and competing strategies in terms of various variance measures.

[1]  Alan J. Mayne,et al.  Introduction to Simulation and SLAM , 1979 .

[2]  Robert G. Sargent,et al.  Validation and verification of simulation models , 1999, Proceedings of the 2004 Winter Simulation Conference, 2004..

[3]  G. Box,et al.  On the Experimental Attainment of Optimum Conditions , 1951 .

[4]  Raymond H. Myers,et al.  Pseudorandom Number Assignment in Quadratic Response Surface Designs , 1987 .

[5]  James M. Lucas,et al.  Which Response Surface Design is Best: A Performance Comparison of Several Types of Quadratic Response Surface Designs in Symmetric Regions , 1976 .

[6]  A. Alan B. Pritsker,et al.  Introduction to simulation and SLAM II , 1979 .

[7]  Russell Schechter,et al.  Introduction to Simulation and SLAM , 1979 .

[8]  G. Arthur Mihram Blockinq in simular experimental designs , 1974 .

[9]  R. C. Bose,et al.  Second Order Rotatable Designs in Three Dimensions , 1959 .

[10]  Margaret J. Robertson,et al.  Design and Analysis of Experiments , 2006, Handbook of statistics.

[11]  N. Draper Small Composite Designs , 1985 .

[12]  Joan M. Donohue,et al.  A sequential experimental design procedure for the estimation of first- and second-order simulation metamodels , 1993, TOMC.

[13]  Philip Heidelberger,et al.  Experiments with initial transient deletion for parallel, replicated steady-state simulations , 1992 .

[14]  G. Box,et al.  A Basis for the Selection of a Response Surface Design , 1959 .

[15]  Averill M. Law,et al.  Simulation Modeling and Analysis , 1982 .

[16]  Raymond H. Myers,et al.  Correlated Simulation Experiments in First-Order Response Surface Design , 1987, Oper. Res..

[17]  J. R. Jackson Networks of Waiting Lines , 1957 .

[18]  Russell R. Barton,et al.  Metamodels for simulation input-output relations , 1992, WSC '92.

[19]  Wheyming Tina Song,et al.  An extension of the multiple-blocks strategy on estimating simulation metamodels , 1996 .

[20]  R. A. Bailey,et al.  Selection of Defining Contrasts and Confounded Effects in Two-level Experiments , 1977 .

[21]  Karl-Rudolf Koch,et al.  Parameter estimation and hypothesis testing in linear models , 1988 .

[22]  Douglas C. Montgomery,et al.  Second-order response surface designs in computer simulation , 1975 .

[23]  G. Arthur Mihram,et al.  An efficient procedure for locating the optimal simular response , 1970 .

[24]  H. O. Hartley,et al.  Smallest Composite Designs for Quadratic Response Surfaces , 1959 .

[25]  Joan M. Donohue,et al.  Simulation designs for quadratic response surface models in the presence of model misspecification , 1992 .

[26]  Lee W. Schruben,et al.  Pseudorandom Number Assignment in Statistically Designed Simulation and Distribution Sampling Experiments , 1978 .

[27]  M. Deaton,et al.  Response Surfaces: Designs and Analyses , 1989 .

[28]  Russell R. Barton Design of experiments for fitting subsystem metamodels , 1997, WSC '97.

[29]  M. F. Franklin Selecting Defining Contrasts and Confounded Effects in p n-m Factorial Experiment , 1985 .