一个模糊的参数模型,用于涉及未知权重环境的F-OWA操作员的决策
Muhammad Touqeer1, Saleh Al Sulaie2, Showkat Ahmad Lone3
1Department of Basic Sciences, University of Engineering and Technology, Taxila 47050, Pakistan.
这项研究引入了一种新的多标准决策 (MCDM) 方法,使用三个梯形模糊数来确定未知环境中的属性权重. 这种方法赋予了较高偏差的属性更大的重要性,增强了决策支持系统.
科学领域:
- 决策科学 决策科学 决策科学
- 模糊的数学 模糊的数学
- 运营研究 运营研究
背景情况:
- 属性权重的确定对于决策支持系统至关重要.
- 现有的方法往往忽略了属性偏差或个人评估.
- 与间隔数相比,模糊数提供了强大的不确定性处理.
研究的目的:
- 提出一种新的多标准决策 (MCDM) 方法.
- 解决未知属性权重的决策问题.
- 通过使用模糊逻辑来增强决策支持系统.
主要方法:
- 使用三条梯形模糊数字 (TTFNs) 进行属性表示.
- 建立基于最大化偏差方法的优化模型.
- 应用模糊顺序加权平均 (F-OWA) 运算符来计算集体偏好.
主要成果:
- 介绍了一种通用的MCDM方法,优于现有运营商.
- 在间隔数和IT2FS上,TFN提供了增强的不确定性表示.
- 该方法有效计算总体偏好值,并确定最理想的替代方案.
结论:
- 拟议的方法提供了在未知权重下对MCDM的更普遍和更有效的方法.
- F-OWA运营商通过考虑属性评级及其排序位置来增强决策.
- 使用TTFN可以在复杂的决策场景中更好地处理不确定性.
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