Important Issues in Multiple Response Optimization
الموضوعات :
1 - Department of Industrial management, Islamic Azad University, Rasht, Iran
الکلمات المفتاحية: Optimization, response surface methodology, Experimental design, Multiple - Response Surface,
ملخص المقالة :
There have been many productive methods developed so far for optimization of multiple response surface (MRS) problems. This paper tends to review the most seminal approaches in MRS and discuss the strength and weakness of each of the approaches through existing aspects in MRS. A numerical example is included to compare results by different methods. Finally some of the prominent areas for future research discussed by different researchers are presented.
[1] Chih–Hua Chiao, Hamada M., Analyzing Experiments with Correlated Multiple Responses, Journal of Quality Technology, 33 (4), 2001.
[2] Del Castillo E., Montgomery D. C., A Nonlinear Programming Solution to the Dual Response Problem, Journal of Quality Technology 25, 199 – 204, 1993.
[3] Del Castillo E., Montgomery D. C., and Mc Carville D. R. Modified Desirability Functions for Multiple Response optimization, Journal of Quality Technology, 28 (3), 337 – 345, 1996.
[4] Harrington E. D. Jr., The Desirability Function, Industrial Quality Control, 494 – 498, 1965.
[5] Khuri A. I., and Conlon M., Simultaneous Optimization of Several Responses Represented by Polynomial Regression Functions, Technometrics, 23, 363 – 375, 1981.
[6] Khuri A., and Cornell J., Response Surfaces: Design and Analyses, Dekker, New York, 1996.
[7] Kim K. J., Byun J. H., Min D., and Jeong, I. J. Multiresponse Surface Optimization: Concept, Methods, and future Directions, (Tutorial), Korea Society for Quality Management, 2001.
[8] Kim K. J., Lin D. K. J., Optimization of multiple Responses Considering both Location and Dispersion Effects, European Journal of Operation Research, 169, 133 – 145, 2006.
[9] Myers R. H., and Montgomery D. C., Response Surface Methodology: Process and Product Optimization Using Designed Experiments, 2nd ed., John Wiley & Sons Inc., New York, 2003.
[10] Nelder J. A., Mead R., A Simplex Method for Function Minimization, Computing Journal 7, 308 – 313, 1965.
[11] Ortiz F., Simpson J. R., and Pignatiello J. J., A Genetic Algorithm Approach, to Multiple – Response Optimization, Journal of Quality Technology, 36 (4), 2004.
[12] Pignatiello J. J., Jr. Strategies for Robust Multi – response Quality Engineering, IIE Trans., 25, 5 – 15, 1993.