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Author (up) Canessa, E.; Vera, S.; Allende, H. pdf  doi
  Title A new method for estimating missing values for a genetic algorithm used in robust design Type
  Year 2012 Publication Engineering Optimization Abbreviated Journal Eng. Optimiz.  
  Volume 44 Issue 7 Pages 787-800  
  Keywords robust design; Taguchi methods; genetic algorithms; response surface methodology  
  Abstract This article presents an improved genetic algorithm (GA), which finds solutions to problems of robust design in multivariate systems with many control and noise factors. Since some values of responses of the system might not have been obtained from the robust design experiment, but may be needed in the search process, the GA uses response surface methodology (RSM) to estimate those values. In all test cases, the GA delivered solutions that adequately adjusted the mean of the responses to their corresponding target values and with low variability. The GA found more solutions than the previous versions of the GA, which makes it easier to find a solution that may meet the trade-off among variance reduction, mean adjustment and economic considerations. Moreover, RSM is a good method for estimating the mean and variance of the outputs of highly non-linear systems, which makes the new GA appropriate for optimizing such systems.  
  Address [Canessa, E.; Vera, S.] Univ Adolfo Ibanez, Fac Ingn & Ciencias, Vina Del Mar, Recreo, Chile, Email:  
  Corporate Author Thesis  
  Publisher Taylor & Francis Ltd Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0305-215x ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000305212800002 Approved  
  Call Number UAI @ eduardo.moreno @ Serial 218  
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