Design Mode Analysis of Pareto Solution Set for Decision-Making Support

Decision making in engineering design problems is challenging because they have multiple and conflicting criteria and complex correlation between design parameters. This study proposes a decision-making support methodology named design mode analysis, which consists of data clustering and principal c...

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Bibliographic Details
Published inJournal of Applied Mathematics Vol. 2014; no. 2014; pp. 643 - 657-472
Main Authors Hiwa, Satoru, Miki, Mitsunori, Hiroyasu, Tomoyuki
Format Journal Article
LanguageEnglish
Published Cairo, Egypt Hindawi Limiteds 2014
Hindawi Publishing Corporation
Hindawi Limited
Wiley
Subjects
Alternatives
Criteria
Decision making
Decomposition
Design
Design engineering
Design parameters
Eigenvectors
Engineering research
Hybrid rocket engines
Mathematical analysis
Mathematical research
Optimization algorithms
Pareto efficiency
Pareto optimality
Pareto optimum
Principal components analysis
Studies
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Summary:Decision making in engineering design problems is challenging because they have multiple and conflicting criteria and complex correlation between design parameters. This study proposes a decision-making support methodology named design mode analysis, which consists of data clustering and principal component analysis (PCA). A design mode is indicated by the eigenvector obtained by PCA and reveals the dominant design parameters in a given dataset. The proposed method is a general framework to obtain the design modes from high-dimensional and large datasets. The effectiveness of the proposed method is verified on the conceptual design problem of the hybrid rocket engine.
Bibliography:ObjectType-Article-1
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ISSN:1110-757X
1687-0042
DOI:10.1155/2014/520209