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Author (up) Canessa, E.; Chaigneau, S. doi  openurl
  Title Response surface methodology for estimating missing values in a pareto genetic algorithm used in parameter design Type Journal Article
  Year 2017 Publication Ingenieria E Investigacion Abbreviated Journal Ing. Invest.  
  Volume 37 Issue 2 Pages 89-98  
  Keywords Robust design; parameter design; pareto genetic algorithm; response surface methodology  
  Abstract We present an improved Pareto Genetic Algorithm (PGA), which finds solutions to problems of robust design in multi-response systems with 4 responses and as many as 10 control and 5 noise factors. Because some response values might not have been obtained in the robust design experiment and are needed in the search process, the PGA uses Response Surface Methodology (RSM) to estimate them. Not only the PGA delivered solutions that adequately adjusted the response means to their target values, and with low variability, but also found more Pareto efficient solutions than a previous version of the PGA. This improvement makes it easier to find solutions that meet the trade-off among variance reduction, mean adjustment and economic considerations. Furthermore, RSM allows estimating outputs' means and variances in highly non-linear systems, making the new PGA appropriate for such systems.  
  Address [Canessa, Enrique] Univ Adolfo Ibanez, Fac Ingn & Ciencias, Santiago, Chile, Email: ecanessa@uai.cl;  
  Corporate Author Thesis  
  Publisher Univ Nac Colombia, Fac Ingenieria Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0120-5609 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000408441100012 Approved no  
  Call Number UAI @ eduardo.moreno @ Serial 760  
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