基于AHP和PROMETHEE的决策支持系统,根据粗略的皮塔哥拉斯模糊集信息来选择篮球队
1Kashi University, Kashi, 844000, China. zhangchaonan2022@163.com.
Scientific reports
|October 22, 2025
概括
本研究介绍了一种使用粗略的毕达哥拉斯模糊集框架进行最佳团队选择的新方法. 开发的方法有效地根据多个标准确定最佳团队,在复杂的场景中增强决策.
科学领域:
- 决策科学 决策科学
- 人工智能的人工智能
- 运营研究 运营研究
背景情况:
- 团队选择是一个复杂的决定,有许多替代方案.
- 在不确定性下,现有的团队选择方法是不够的.
- 多属性决策 (MADM) 为复杂的选择提供了一个框架.
研究的目的:
- 介绍一个新的聚合运算符,粗略的毕达哥拉斯模糊多比加权平均 (RPyFDWA) 运算符.
- 应用分析层次过程 (AHP) 来测量重量和PROMETHEE来排名替代品.
- 开发一个强大的框架来选择使用粗皮达哥拉斯模糊集 (RPyFS) 的团队来处理不确定性.
主要方法:
- 在RPyFS框架内开发RPyFDWA运营商.
- 整合了AHP用于属性权重和PROMETHEE用于替代排名.
- 运算符的属性 (idempotency,单调性,边界性) 的数学验证.
主要成果:
- 拟议的RPyFDWA运营商和PROMETHEE方法在篮球案例研究中成功确定了最佳团队.
- 与现有方法相比,RPyFS框架证明了对不确定的数据的处理优越.
- 灵敏度分析证实了模型的可靠性和输入变量的影响.
结论:
- 新的RPyFDWA运算符为复杂的团队选择问题提供了灵活和有效的工具.
- 综合AHP-RPyFDWA-PROMETHEE方法提供了一个有效和可靠的方法,用于在不确定性下做出决定.
- 这项研究将MADM技术用于体育和专业环境中的实际应用.
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