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A Piecewise Linear FGM Approach for Efficient and Accurate FAHP Analysis: Smart Backpack Design as an Example

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  • Hsin-Chieh Wu

    (Department of Industrial Engineering and Management, Chaoyang University of Technology, Taichung 41349, Taiwan)

  • Toly Chen

    (Department of Industrial Engineering and Management, National Chiao Tung University, 1001, University Road, Hsinchu 300, Taiwan)

  • Chin-Hau Huang

    (Department of Industrial Engineering and Management, National Chiao Tung University, 1001, University Road, Hsinchu 300, Taiwan
    Department of Computer-Aided Industrial Design, Overseas Chinese University, 100, Chiao Kwang Road, Seatwen, Taichung City 407, Taiwan)

Abstract

Most existing fuzzy AHP (FAHP) methods use triangular fuzzy numbers to approximate the fuzzy priorities of criteria, which is inaccurate. To obtain accurate fuzzy priorities, time-consuming alpha-cut operations are usually required. In order to improve the accuracy and efficiency of estimating the fuzzy priorities of criteria, the piecewise linear fuzzy geometric mean (PLFGM) approach is proposed in this study. The PLFGM method estimates the α cuts of fuzzy priorities and then connects these α cuts with straight lines. As a result, the estimated fuzzy priorities will have piecewise linear membership functions that resemble the real shapes. The PLFGM approach has been applied to the identification of critical features for a smart backpack design. According to the experimental results, the PLFGM approach improved the accuracy and efficiency of estimating the fuzzy priorities of these critical features by 33% and 80%, respectively.

Suggested Citation

  • Hsin-Chieh Wu & Toly Chen & Chin-Hau Huang, 2020. "A Piecewise Linear FGM Approach for Efficient and Accurate FAHP Analysis: Smart Backpack Design as an Example," Mathematics, MDPI, vol. 8(8), pages 1-18, August.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:8:p:1319-:d:396298
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    References listed on IDEAS

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