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集团决策框架使用广义的赫罗尼亚平均运算符在准阶层的orthopair模糊环境与应用程序
Muhammad Bilal1, Jawad Ali2, Muhammad Fawad Tariq3
1School of Mathematics and Statistics, Yunnan University, Yunnan, 650091, China.
Scientific reports
|April 16, 2025
概括
这项研究为模糊数据引入了新的决策工具,增强了复杂的相互依存关系的分析. 开发的方法可以更好地处理特定的模糊数字类型,从而使项目和大学选择更有效.
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:
- 在复杂的系统中,有效的决策需要强大的方法来处理不确定和相互依存的数据.
- 现有的模糊集合理论,如一般化的赫罗尼平均值和几何赫罗尼平均值运算符,在捕捉特定模糊数结构内的相关性方面存在局限性.
- 在决策过程中,pq等级的正对偶模糊 (pqQROF) 数值结构对相互依赖性分析提出了独特的挑战.
研究的目的:
- 为了将概括的赫罗尼平均值和几何赫罗尼平均值运算符扩展到pqQROF数环境中.
- 开发一种新的混合决策框架,将距离测量,排名和和 (RS) 方法和聚合运算符集成在一起,以确定客观和主观标准权重.
- 通过实践案例研究和比较分析,验证拟议框架的有效性.
主要方法:
- 扩展赫罗尼平均值和几何赫罗尼平均值运算符以适应pqQROF数.
- 开发一种混合决策模型,采用新的距离测量和RS方法来确定重量.
- 将开发的框架应用于项目选择和大学选择问题.
主要成果:
- 成功地将赫罗尼安和几何赫罗尼安平均运算符扩展到pqQROF设置,从而实现相关性分析.
- 在实际场景 (项目和大学选择) 中证明混合决策框架的有效性.
- 对比分析,表明拟议的决策算法在现有方法上的优越性.
结论:
- 拟议的扩展运算符和混合决策框架有效地解决了处理pqQROF数内的相关性现有方法的局限性.
- 开发的方法为涉及模糊数据的复杂决策问题提供了更准确,更可靠的工具.
- 该研究强调了模糊决策方法的重大进步,特别是在相互依赖的数据结构方面.
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