Combining iterative heuristic optimization and uncertainty analysis methods for robust parameter design

dc.contributor.authorJosé Delpiano
dc.contributor.authorMarcos Sepúlveda
dc.coverage.spatialBolivia
dc.date.accessioned2026-03-22T15:42:48Z
dc.date.available2026-03-22T15:42:48Z
dc.date.issued2006
dc.descriptionCitaciones: 7
dc.description.abstractA number of investigators have pointed out that products and processes lack quality because of performance inconsistency, which is often due to uncontrollable parameters in the manufacturing process or product usage. Robust design methods are aimed at finding product/process designs that are less sensitive to parameter variation. Robust design of computer simulations requires a large number of runs, which are very time consuming. A novel methodology for robust design is presented in this article. It integrates an iterative heuristic optimization method with uncertainty analysis to achieve effective variability reductions, exploring a large parameter domain with an accessible number of simulations. To demonstrate the effectiveness of this methodology, the robust design of a 0.15 μm CMOS device is shown.
dc.identifier.doi10.1080/03052150600747079
dc.identifier.urihttps://doi.org/10.1080/03052150600747079
dc.identifier.urihttps://andeanlibrary.org/handle/123456789/53973
dc.language.isoen
dc.publisherTaylor & Francis
dc.relation.ispartofEngineering Optimization
dc.sourceUniversidad de Los Andes, Chile
dc.subjectHeuristic
dc.subjectComputer science
dc.subjectMathematical optimization
dc.subjectRobust optimization
dc.subjectDesign of experiments
dc.subjectProcess (computing)
dc.subjectEngineering design process
dc.subjectProduct (mathematics)
dc.subjectUncertainty analysis
dc.subjectIterative design
dc.titleCombining iterative heuristic optimization and uncertainty analysis methods for robust parameter design
dc.typearticle

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