Institute of Numerical Sciences, Kohat University of Science and Technology, Kohat, KPK, Pakistan.
Department of Mathematical Sciences, United Arab Emirates University, Al‑Ain, UAE.
PLoS One. 2024 May 20;19(5):e0297462. doi: 10.1371/journal.pone.0297462. eCollection 2024.
Considering the advantages of q-rung orthopair fuzzy 2-tuple linguistic set (q-RFLS), which includes both linguistic and numeric data to describe evaluations, this article aims to design a new decision-making methodology by integrating Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and qualitative flexible (QUALIFLEX) methods based on the revised aggregation operators to solve multiple criteria group decision making (MCGDM). To accomplish this, we first revise the extant operational laws of q-RFLSs to make up for their shortcomings. Based on novel operational laws, we develop q-rung orthopair fuzzy 2-tuple linguistic (q-RFL) weighted averaging and geometric operators and provide the corresponding results. Next, we develop a maximization deviation model to determine the criterion weights in the decision-making procedure, which accounts for partial weight unknown information. Then, the VIKOR and QUALIFLEX methodologies are combined, which can assess the concordance index of each ranking combination using group utility and individual maximum regret value of alternative and acquire the ranking result based on each permutation's general concordance index values. Consequently, a case study is conducted to select the best bike-sharing recycling supplier utilizing the suggested VIKOR-QUALIFLEX MCGDM method, demonstrating the method's applicability and availability. Finally, through sensitivity and comparative analysis, the validity and superiority of the proposed method are demonstrated.
考虑到 q-rung 对偶模糊 2-元语言集（q-RFLS）的优势，它包含语言和数字数据来描述评估，本文旨在设计一种新的决策方法，通过整合基于修订的聚合算子的 Vlsekriterijumska Optimizacija I Kompromisno Resenje（VIKOR）和定性灵活（QUALIFLEX）方法来解决多准则群体决策（MCGDM）问题。为了实现这一目标，我们首先修订了 q-RFLS 的现有运算定律，以弥补其不足。基于新的运算定律，我们开发了 q-rung 对偶模糊 2-元语言（q-RFL）加权平均和几何算子，并提供了相应的结果。接下来，我们开发了一个最大化偏差模型来确定决策过程中的准则权重，该模型考虑了部分权重未知信息。然后，结合 VIKOR 和 QUALIFLEX 方法，可以使用群体效用和替代方案的个体最大后悔值来评估每个排序组合的一致性指数，并根据每个排列的总一致性指数值获得排序结果。因此，使用所提出的 VIKOR-QUALIFLEX MCGDM 方法进行了案例研究，以选择最佳的共享单车回收供应商，展示了该方法的适用性和可用性。最后，通过敏感性和比较分析，验证了所提出方法的有效性和优越性。
