Scholarlink

<p>Although fuzzy multi-criteria group decision-making methods have been employed into group design evaluation (GDE) to handle the uncertainty of individual linguistic preference, they overlooked the group-level uncertainty hidden in a group of preferences. To address this problem, this study attempts to characterize such uncertainty as the global fuzziness of preference data. Based on linguistic D-number (LDN) theory, we propose a new concept of triplet-composed preference (T-preference) that consists of preference, reliability and fuzziness information. Accordingly, the novel T-preference generation method and T-preference-based GDE method (GDE-TP) are presented. The objective of GDE-TP is to make the design evaluation more rational by comprehensively considering the preference, reliability, and fuzziness factors. Under the principle of GDE-TP, the optimal design candidate is the one with high and reliable preference, while maintaining low fuzziness. An example and empirical analysis has been carried out in this study, which show that: (1) GDE-TP makes more reasonable decision than traditional fuzzy evaluation approaches; (2) compared to reliability factor, the fuzziness factor has a greater influence on the group decision-making; (3) GDE-TP is robust to different decision-making mechanisms; iv) GDE-TP is also robust to different groups of design attributes. The resources are available at: <a href="https://www.scidb.cn/s/z2iyem">https://www.scidb.cn/s/z2iyem</a>.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Fuzzy multi-criteria group decision-making method based on triplet-composed preference considering the group-level uncertainty in design evaluation

  • 期刊论文

  • 发表日期：

    2026年6月19日

查看全文
  • Jin Qi,
  • Jin Ma,
  • Bin Chen

摘要

Although fuzzy multi-criteria group decision-making methods have been employed into group design evaluation (GDE) to handle the uncertainty of individual linguistic preference, they overlooked the group-level uncertainty hidden in a group of preferences. To address this problem, this study attempts to characterize such uncertainty as the global fuzziness of preference data. Based on linguistic D-number (LDN) theory, we propose a new concept of triplet-composed preference (T-preference) that consists of preference, reliability and fuzziness information. Accordingly, the novel T-preference generation method and T-preference-based GDE method (GDE-TP) are presented. The objective of GDE-TP is to make the design evaluation more rational by comprehensively considering the preference, reliability, and fuzziness factors. Under the principle of GDE-TP, the optimal design candidate is the one with high and reliable preference, while maintaining low fuzziness. An example and empirical analysis has been carried out in this study, which show that: (1) GDE-TP makes more reasonable decision than traditional fuzzy evaluation approaches; (2) compared to reliability factor, the fuzziness factor has a greater influence on the group decision-making; (3) GDE-TP is robust to different decision-making mechanisms; iv) GDE-TP is also robust to different groups of design attributes. The resources are available at: https://www.scidb.cn/s/z2iyem.