在 q-rung orthopair fuzzy 2-tuple 语言上下文下的集成群体决策方法,具有部分权重信息
Fatima Abbas1, Jawad Ali1, Wali Khan Mashwani1
1Institute of Numerical Sciences, Kohat University of Science and Technology, Kohat, KPK, Pakistan.
PloS one
|May 20, 2024
概括
本研究引入了一种使用模糊逻辑和集成VIKOR-QUALIFLEX方法的新决策方法,用于复杂的集团决策. 该方法通过语言和数字数据来增强评估,在供应商选择中证明有效.
科学领域:
- 决策科学 决策科学
- 模糊逻辑系统 模糊逻辑系统
- 运营研究 运营研究
背景情况:
- 传统的决策方法与不准确的语言和数字数据作斗争.
- q-rung orthopair fuzzy 2-tuple语言集 (q-RFLS) 为处理复杂的评估提供了一个强大的框架.
- 集成多重标准组决策 (MCGDM) 需要先进的方法.
研究的目的:
- 通过整合 VIKOR 和 QUALIFLEX 方法,开发一种新的 MCGDM 方法.
- 通过修订运营法律和开发新的聚合运营商来加强q-RFLS.
- 解决确定标准权重的挑战,特别是在部分未知信息的情况下.
主要方法:
- 对q-rung orthopair fuzzy 2-tuple语言集 (q-RFLSs) 的运行法律的修订.
- 开发了q-rung orthopair fuzzy 2-tuple语言 (q-RFL) 的加权平均和几何运算符.
- 将VIKOR和QUALIFLEX方法与标准权重的最大化偏差模型集成.
- 将组合方法应用于供应商选择的现实世界案例研究.
主要成果:
- 为q-RFLS成功开发了新的运行规则和聚合运营商.
- 建立了一个结合VIKOR和QUALIFLEX的强大的MCGDM方法.
- 提出的方法证明了在选择共享自行车回收供应商时的适用性和可用性.
- 敏感性和比较分析证实了新方法的有效性和优越性.
结论:
- 拟议的VIKOR-QUALIFLEX MCGDM方法有效地处理使用语言和数字数据的复杂决策问题.
- 修订后的q-RFLS框架和新运营商为模糊决策分析提供了增强的能力.
- 该研究证实了综合方法在现实应用中的实用实用性和优越性.
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