在MCDA中的和规范化:对排名稳定性的数据驱动视角
1Faculty of Computer Science, Bialystok University of Technology, Wiejska 45A, 15-351 Bialystok, Poland.
Entropy (Basel, Switzerland)
|January 28, 2026
概括
多重标准决策分析 (MCDA) 中的规范化技术显著影响排名稳定性. 这项研究揭示了数据如何影响这些规范化方法,为可靠的决策提供了基于的方法.
科学领域:
- 运营研究 运营研究
- 决策科学 决策科学 决策科学
- 信息理论 信息理论
背景情况:
- 在多重标准决策分析 (MCDA) 中,规范化对于比较异质数据至关重要.
- 不同的规范化技术可能会导致不同的排名,导致决策结果的不确定性.
- 标准数据的结构,特别是它的,影响了规范化行为和排名稳定性.
研究的目的:
- 在TOPSIS框架内检查七种常见的规范化技术的行为 (通过与理想解决方案相似的订单偏好技术).
- 分析标准数据结构,特别是,如何影响规范化结果和排名稳定性.
- 提出基于的方法来选择规范化技术,以提高MCDA的透明度和稳定性.
主要方法:
- 对七种规范化程序 (矢量,最大,线性和,最大-最小) 的分析,考虑数学属性,灵敏度和成本标准处理.
- 使用香农作为信息分散和标准数据中的结构不确定性的衡量标准.
- 一项实验性研究,使用十个替代方案和四个标准 (高和低) 来证明在规范化效应中的调解作用.
主要成果:
- 单独的规范化选择可以导致偏好值和排名的实质差异.
- 高度标准通常会导致稳定的排名,而低度标准会放大灵敏度,特别是在极端或成本类型数据.
- 作为数据结构和正常化诱导的排名变化之间的关键调解者.
结论:
- 规范化技术的选择对MCDA结果产生重大影响,发挥了关键的调解作用.
- 低度标准更容易受到等级不稳定性引起的规范化,特别是在具有挑战性的数据类型.
- 基于的方法可以提高MCDA中规范化选择的方法透明度和稳定性.
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