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Xue and Ji (2001) proposed a methodology for dealing with angular features in tolerance charting.
This paper presents a novel methodology for dealing with decision-making problems in product design fields.
It thus provides a methodology for dealing with uncertainty in the prior knowledge.
The main contribution of the paper is to propose a fully statistical methodology for dealing with non-linear nuisance parameters.
It has long been a problem of finding out a proper methodology for dealing with multiscale complex systems, including processes and products.
Recently, the combination of sliding mode and fuzzy logic techniques has emerged as a promising methodology for dealing with nonlinear, uncertain, dynamical systems.
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These later papers, by they way, use a variety of methodologies for dealing with non-linearity and also for trying to determine causation.
A number of technical advances will likely improve the usefulness of models, including rigorous methodologies for dealing with missing and uncertain information; improved methods for interpretation of multivariate data sets and for multi-objective decision making involving trade-offs among conflicting goals; and novel modelling methods as alternatives to traditional mathematical models.
We anticipate that more and more pathway-based methodologies for dealing with this new data type will appear in the near future.
A modelling methodology developed for dealing with fatigue failures on large boiler tube assemblies, as used by power generation industries, is described.
All of these suggest the pressing need of new methodologies designed for dealing with MaOPs, new performance metrics and benchmark functions tailored for experimental and comparative studies of evolutionary many-objective optimization (EMaO) algorithms.
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