一个基于相对投影的多属性组决策模型,与非合作行为管理和应用到NEV供应商选择
IEEE transactions on cybernetics
|August 6, 2024
概括
这项研究引入了一个新的共识模型,用于评估替代方案的专家,考虑认知和利益冲突. 该模型有效地管理非合作行为 (NCB),以提高决策效率.
科学领域:
- 决策科学 决策科学
- 运营研究 运营研究
- 人工智能的人工智能
背景情况:
- 传统的共识模型往往忽视了不同专家组之间的认知和利益冲突的复杂相互作用.
- 同时解决内部和外部专家冲突,特别强调内部专家的兴趣和外部专家的认知,提出了一个新的挑战.
研究的目的:
- 开发一种新的共识模型,将内部和外部专家的认知和利益冲突整合在一起.
- 在专家中引入分类和管理非合作行为 (NCB) 的方法.
- 提高在多属性小组决策中达成共识的效率.
主要方法:
- 建议基于相对投影的索引来量化认知和利益冲突,使用多属性偏好矩阵 (MAPM) 和属性权重向量.
- 开发了三类专家分类系统,并为国家央行制定了量身定制的管理策略.
- 引入了一个共识机制,包括MAPM调整,相互评估矩阵 (MEM) 和基于惩罚的专家权重更新系统.
- 设计了一个算法来捕捉达成共识,通过参数区分内部和外部专家.
主要成果:
- 拟议的模型有效地分类和管理专家非合作行为 (NCB).
- 协商一致机制,包括调整和处罚功能,有助于达成可接受的协商一致水平.
- 该模型在新能源汽车电池供应商选择的现实应用中展示了提高达成共识的效率.
结论:
- 新的共识模型为与相互矛盾的专家进行多属性小组决策提供了一个强大的框架.
- 与国家央行一起有效管理认知和利益冲突,大大提高了共识效率.
- 该模型为复杂的选择问题提供了一个实用的工具,例如在新能源汽车行业.
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