大规模的群体共识多属性决策方法基于概率的双犹的模糊集
Yuting Zhu1, Wenyu Zhang1,2, Junjie Hou1
1China Aerospace Academy of Systems Science and Engineering, Beijing 100048, China.
Mathematical biosciences and engineering : MBE
|March 29, 2024
概括
一种用于大规模集团决策的新共识方法使用概率学双犹模糊集来量化专家意见. 这种方法可以在复杂的模糊环境中提高决策能力,拥有20多名专家.
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:
- 在模糊环境中进行大规模的集团决策存在重大挑战.
- 现有的方法很难有效地整合各种各样的专家意见和不确定性.
- 量化专家判断,包括会员和非会员程度,对于稳健的决策结果至关重要.
研究的目的:
- 引入一种新的大型群体共识多属性决策方法.
- 在模糊的环境中与众多专家一起解决决策的复杂性.
- 为了有效量化和整合专家决策信息,使用概率学双犹的模糊集合.
主要方法:
- 构建一个概率的双犹的模糊信息评估矩阵,并确定属性权重.
- 根据有效性标准对专家组进行分类和选择最佳方案.
- 实施达成共识和信息整合模型,以实现同步决策.
主要成果:
- 一种用于大规模群体共识多属性决策的验证方法.
- 在城市应急能力评估的案例研究中证明了有效性.
- 通过对替代决策方法进行比较分析表明的优越性.
结论:
- 拟议的方法有效地处理模糊环境中的大规模集团决策.
- 概率学双犹模糊集为量化专家不确定性提供了一个强大的框架.
- 该方法为需要共识的复杂决策场景提供了优越的方法.
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