Journal article
Design Optimization Problem Reformulation Using Singular Value Decomposition
Journal of mechanical design (1990), v 131(8), pp 0810061-08100610
01 Aug 2009
Abstract
This paper presents a design optimization problem reformulation method based on singular value decomposition, dimensionality reduction, and unsupervised clustering. The method calculates linear approximations of associative patterns of symbol co-occurrences in a design problem representation to induce implicit coupling strengths between variables and constraints. Unsupervised clustering of these approximations is used to heuristically identify useful reformulations. In contrast to knowledge-rich Artificial Intelligence methods, this method derives from a knowledge-lean, unsupervised pattern recognition perspective. We explain the method on an analytically formulated decomposition problem, and apply it to various analytic and nonanalytic problem forms to demonstrate design decomposition and design "case" identification. A single method is used to demonstrate multiple design reformulation tasks. The results show that the method can be used to infer multiple well-formed reformulations starting from a single problem representation in a knowledge-lean manner.
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Details
- Title
- Design Optimization Problem Reformulation Using Singular Value Decomposition
- Creators
- Somwrita Sarkar - The University of SydneyAndy Dong - The University of SydneyJohn S. Gero - George Mason University
- Publication Details
- Journal of mechanical design (1990), v 131(8), pp 0810061-08100610
- Publisher
- Asme
- Number of pages
- 10
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Psychological and Brain Sciences (Psychology)
- Web of Science ID
- WOS:000268440400007
- Scopus ID
- 2-s2.0-77955178618
- Other Identifier
- 991022156307304721