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<p>In response to the decision-making challenges posed by large-scale information and complex data sources in civil aviation airport site selection, this paper proposes a novel method that integrates group consensus within a framework of substantial uncertainty. The method comprises five key processes: (1) Evaluation process: Based on the constructed multicriteria evaluation system for airport site selection, the q-Rung Orthopair Fuzzy (q-ROF) information is employed to represent evaluations from large-scale decision makers, which effectively characterizes the uncertainty of information and broadens the evaluative scope. (2) Clustering process: A clustering procedure is designed for large-scale q-ROF evaluation data and weight information of criteria, identifying and removing outliers. (3) Consensus reaching process: Considering the characteristics of q-ROF evaluations and multiplicative preference relations, two adaptive consensus reaching algorithms are developed to enhance group consensus levels, thereby improving the rationality of decision-making results. (4) Weight determination process: Criteria and subcriteria weights are calculated using multiplicative preference weighting approach and a deviation maximization model, respectively, derived from aggregated group evaluations. (5) Ranking process: The q-ROF Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method is applied, in conjunction with the induced q-ROF information integration paradigm, to comprehensively rank the alternative sites. Finally, the feasibility and effectiveness of the proposed method are demonstrated through a case study of civil aviation branch airport planning in a specific city.</p>

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Research on Civil Aviation Airport Site Selection Considering Group Consensus Level Under Large-Scale Uncertain Information

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年5月5日

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  • Rui Wang,
  • Jing-Han Zeng,
  • Jing-Yang Huang,
  • Rui Kang,
  • Jiang Yuan,
  • Qing-Wei Zhong

摘要

In response to the decision-making challenges posed by large-scale information and complex data sources in civil aviation airport site selection, this paper proposes a novel method that integrates group consensus within a framework of substantial uncertainty. The method comprises five key processes: (1) Evaluation process: Based on the constructed multicriteria evaluation system for airport site selection, the q-Rung Orthopair Fuzzy (q-ROF) information is employed to represent evaluations from large-scale decision makers, which effectively characterizes the uncertainty of information and broadens the evaluative scope. (2) Clustering process: A clustering procedure is designed for large-scale q-ROF evaluation data and weight information of criteria, identifying and removing outliers. (3) Consensus reaching process: Considering the characteristics of q-ROF evaluations and multiplicative preference relations, two adaptive consensus reaching algorithms are developed to enhance group consensus levels, thereby improving the rationality of decision-making results. (4) Weight determination process: Criteria and subcriteria weights are calculated using multiplicative preference weighting approach and a deviation maximization model, respectively, derived from aggregated group evaluations. (5) Ranking process: The q-ROF Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method is applied, in conjunction with the induced q-ROF information integration paradigm, to comprehensively rank the alternative sites. Finally, the feasibility and effectiveness of the proposed method are demonstrated through a case study of civil aviation branch airport planning in a specific city.