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Low‐cost response surface methods from simulation optimization
Author(s) -
Allen Theodore T.,
Yu Liyang
Publication year - 2002
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.440
Subject(s) - response surface methodology , computer science , mathematical optimization , design of experiments , surface (topology) , box–behnken design , reliability engineering , mathematics , engineering , statistics , machine learning , geometry
We propose ‘low‐cost response surface methods’ (LCRSMs) that typically require half the experimental runs of standard response surface methods based on central composite and Box Behnken designs, but yield comparable or lower modeling errors under realistic assumptions. In addition, the LCRSMs have substantially lower modeling errors and greater expected savings compared with alternatives with comparable numbers of runs, including small composite designs and computer‐generated designs based on popular criteria such as D‐optimality. The LCRSM procedures appear to be the first experimental design methods derived as the solution to a simulation optimization problem. Together with modern computers, simulation optimization offers unprecedented opportunities for applying clear, realistic multicriterion objectives and assumptions to produce useful experimental design methods. We compare the proposed LCRSMs with alternatives based on six criteria. We conclude that the proposed methods offer attractive alternatives when the experimenter is considering dropping factors to use standard response surface methods or would like to perform relatively few runs and stop with a second‐order model. Copyright © 2002 John Wiley & Sons, Ltd.