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AN IMPROVED MULTIVARIATE LOSS FUNCTION APPROACH TO OPTIMIZATION 被引量:2

AN IMPROVED MULTIVARIATE LOSS FUNCTION APPROACH TO OPTIMIZATION
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摘要 The basic purpose of a quality loss function is to evaluate a loss to customers in a quantitativemanner.Although there are several multivariate loss functions that have been proposed and studied inthe literature,it has room for improvement.A good multivariate loss function should represent anappropriate compromise in terms of both process economics and the correlation structure amongvarious responses.More important,it should be easily understood and implemented in practice.According to this criterion,we first introduce a pragmatic dimensionless multivariate loss functionproposed by Artiles-Leon,then we improve the multivariate loss function in two respects:one ismaking it suitable for all three types of quality characteristics;the other is considering correlationstructure among the various responses,which makes the improved multivariate loss function moreadequate in the real world.On the bases of these,an example from industrial practice is provided tocompare our improved method with other methods,and last,some reviews are presented inconclusion. The basic purpose of a quality loss function is to evaluate a loss to customers in a quantitativemanner.Although there are several multivariate loss functions that have been proposed and studied inthe literature,it has room for improvement.A good multivariate loss function should represent anappropriate compromise in terms of both process economics and the correlation structure amongvarious responses.More important,it should be easily understood and implemented in practice.According to this criterion,we first introduce a pragmatic dimensionless multivariate loss functionproposed by Artiles-Leon,then we improve the multivariate loss function in two respects:one ismaking it suitable for all three types of quality characteristics;the other is considering correlationstructure among the various responses,which makes the improved multivariate loss function moreadequate in the real world.On the bases of these,an example from industrial practice is provided tocompare our improved method with other methods,and last,some reviews are presented inconclusion.
出处 《Systems Science and Systems Engineering》 CSCD 2004年第3期318-325,共8页 系统科学与系统工程学报(英文版)
基金 ThisworkissupportedbytheNationalNaturalScienceFoundationofChinaunderGrant79900018]AeronauticalScienceFoundationofChinaunderGrant02J55001
关键词 Multivariate loss function CORRELATION OPTIMIZATION principal component analysis Multivariate loss function correlation optimization principal component analysis
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参考文献11

  • 1[1]Ames, A.E., MacDonald, S., Mattucci, N.,Szonyi, G., Hawkins, D.M, "Quality loss functions for optimization across multiple response surfaces", Journal of Quality Technology, Vol. 29, No. 3, pp339-346,1997.
  • 2[2]Artiles-Leon, N., "A pragmatic approach to multi-response problems using loss functions", Quality Engineering, Vol. 9, No.2, pp213-220, 1996-97.
  • 3[3]Derringer, G., Suich, R., "Simultaneous optimization of several response variables",Journal of Quality Technology, Vol. 12, No.4, pp214-219, 1980.
  • 4[4]Kapur, C.K., Cho, B.R., "Economic design of the specification region for multiple quality characteristics", IIE Transactions,Vol. 28, pp237-248, 1996
  • 5[5]Khuri, A. I., Conlon. M.., "Simultaneous optimization of multiple responses represented by polynomial regression functions", Technometrics, Vol. 23,pp363-375, 1981.
  • 6[6]Mastrangelo, C.G., Runger, G.C.,Montgomery, D.C., "Statistical process monitoring with principal components",Quality and Reliability Engineering International, Vol. 12, No. 2, pp203-210,1996.
  • 7[7]Montgomery, D. C., Design and Analysis of Experiments, 5th Ed, John Wiley & Sons,New York, 2001.
  • 8[8]Pignatiello, J. J. Jr., "Strategies for robust multiresponse quality engineering", IIE Transactions, Vol. 25, No. 3, pp5-15, 1993.
  • 9[9]Suhr, R., Batson, R. G., "Constrained multivariate loss function minimization",Quality Engineering, Vol. 13, No. 3,pp475-483, 2001.
  • 10[10]Vining, G.G., "A compromise approach to multiresponse optimization", Journal of Quality Technology, Vol. 30, No. 4,pp309-313, 1998.

同被引文献14

  • 1黄洪钟,刘鸿莉,古莹奎,张旭.基于物理规划的模糊稳健优化设计[J].清华大学学报(自然科学版),2005,45(8):1020-1022. 被引量:6
  • 2马义中,赵逢禹.多元质量特性的稳健设计及其实现[J].系统工程与电子技术,2005,27(9):1580-1582. 被引量:20
  • 3郭惠昕.基于混合遗传算法的谐波齿轮传动优化设计[J].农业机械学报,2006,37(7):121-124. 被引量:10
  • 4Taguchi G. Introduction to quality engineering: designing quality into products and processes [M]. Tokyo: Asian Productivity Organization, 1986.
  • 5Suh N P. Axiomatic design-advances and applications[ M]. New York: Oxford University Press, 2001.
  • 6Rinderle J R. Suh N P. Measures of functional coupling in design[J]. Transactions of ASME, Journal of Engineering for Industry, 1982, 104(4) :383-388.
  • 7Guo H. Robust design for quality reliability via fuzzy probability[C] ffAdvanced Reliability Modeling: Proceeding of the 2004 Asian International Workshop on Advanced Reliability Modeling, Singapore: World Scientific Publishing Co. Pte. Ltd., 2004:149- 156.
  • 8陈立周.稳健设计[M].北京:机构工业出版社,1999..
  • 9Nair V N. Taguchi' s parameter design: a panel discussion [J].Technometrics, 1992, 34(2): 121 - 161.
  • 10Robinson T J, Borror C M, Myers R H. Robust parameter design:A review [J]. ‘ Quality and Reliability Engineering International, 2004, 20(1): 81-101.

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