在T球模糊信息管理中的多重标准决策分析方法
1Department of Industrial and Business Management, Graduate Institute of Management, Chang Gung University, No. 259, Wenhua 1st Rd., Guishan District, Taoyuan City, 33302 Taiwan.
Artificial intelligence review
|June 26, 2023
概括
本研究引入了一种使用T球模糊 (T-SF) 集的新决策方法,用于处理多标准评估中的复杂不确定性. 开发的评估机制和T-SF Minkowski距离指数在不确定的情况下提高了决策准确性和可靠性.
科学领域:
- 决策科学 决策科学
- 模糊的集合理论 模糊的集合理论
- 运营研究 运营研究
背景情况:
- 传统的模糊集合与复杂的不确定性作斗争,导致信息丢失.
- 图球模糊 (T-SF) 集提供了一个更强大的框架,使用四个成员级来捕捉微妙的不确定性.
- 现有的多标准决策 (MCDA) 方法需要在高度不确定的环境中进行增强.
研究的目的:
- 开发一种基于T球模糊 (T-SF) 集的新型评估机制和决策分析方法.
- 引入以T-SF相关性为导向的测量和T-SF明科夫斯基距离指数,以增强MCDA.
- 解决涉及不确定性和多重标准的复杂决策问题.
主要方法:
- 开发以T-SF相关性为导向的测量,利用最大和平方根函数.
- 使用T-SF Minkowski距离指数集成超级/超级标识符.
- 构建T-SF决策分析程序,包括评估意义,最大化/最小化和全球超级排名指数.
主要成果:
- 成功开发和验证了一种新的T-SF决策分析方法和评估机制.
- 拟议的方法在具体的位置选择问题上证明了有效性,显示了适应性和可靠性.
- 敏感性分析证实了选项之间的衍生优势关系的稳定性.
结论:
- T-SF决策分析方法提供了一种可靠和灵活的方法,用于在不确定性下做出决策.
- 建议使用固定的理想/反理想基准测试机制,因为它易于使用和灵敏.
- 该研究推进了处理T-SF信息在复杂决策场景中的计算工具.
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