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

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  • Satoru Hiwa
  • Tomoyuki Hiroyasu
  • Mitsunori Miki

Abstract

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.

Suggested Citation

  • Satoru Hiwa & Tomoyuki Hiroyasu & Mitsunori Miki, 2014. "Design Mode Analysis of Pareto Solution Set for Decision-Making Support," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-15, November.
    • Handle: RePEc:hin:jnljam:520209
    DOI: 10.1155/2014/520209
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