Article ID: | iaor1997435 |
Country: | Switzerland |
Volume: | 25 |
Issue: | 1 |
Start Page Number: | 45 |
End Page Number: | 64 |
Publication Date: | Aug 1995 |
Journal: | Engineering Optimization |
Authors: | Mistree F., Allen J.K., Vadde S. |
Keywords: | optimization, engineering |
Catalog design is a procedure in which a system is assembled by selecting standard components from catalogs of available components. Selection in design involves making a choice among a number of alternatives based on several attributes. The information available to a designer during the early stages of project initiation may be uncertain. A designer then has to balance limited resources against the quality of solution. This complex task becomes formidable when dealing with coupled selection problems, that is problems which must be solved simultaneously. Coupled selection problems share a number of coupling attributes. An earlier paper has shown how selection problems, both coupled and uncoupled can be reformulated as a single compromise Decision Support Problem (DSP) using a deterministic model. This paper shows how to extend this to a nondeterministic case. Fuzzy set theory is used to model imprecision and Bayesian statistics to model stochastic information. Formulations with solution schemes are presented to handle both fuzzy and stochastic information in the standard framework of a compromise DSP. The approaches are illustrated by an example involving the coupled selection of a heat exchanger concept and a cooling fluid to be used on a marine drilling rig. The emphasis in this paper is placed on the method rather than the results