一个战略决策框架,用于评估绿色供应链管理的障碍,使用分数模糊相似度衡量
Salma Khan1, Muhammad I Syam2, Hamza Ali Abujabal3
1Department of Mathematics and Statistics, Hazara University, Mansehra, 21300, KPK, Pakistan. salmakhan359@gmail.com.
Scientific reports
|August 8, 2025
概括
新的模糊集相似度措施通过使用分数指数来提高成员级别的决策能力. 这种方法可以更好地处理复杂问题的不确定性,提供更灵活,更准确的结果.
科学领域:
- 模糊的集合理论 模糊的集合理论
- 决策分析 决策分析
- 计算智能是一种计算智能.
背景情况:
- 类似性和距离的测量对于理解决策中的模糊集关系至关重要.
- 对于包括分数模糊集合在内的概括模糊集的现有测量方法,对于 [公式:参见文本] 分数模糊集的测量方法是有限的.
- 这种限制阻碍了模糊模型在复杂,不确定的决策任务中的有效性.
研究的目的:
- 为 [公式:参见文本] 分数模糊集合引入新的相似度.
- 为了提高捕捉模糊价值关系的灵活性和细节性.
- 将这些措施应用于不确定的环境的决策模型中.
主要方法:
- 开发了新的相似度,使用三个独立的分数指数来衡量会员,中立和非会员的程度.
- 将这些措施整合到一个多标准决策 (MCDM) 框架中.
- 通过现实世界的案例研究验证了拟议的方法.
主要成果:
- 新的相似度措施提供了更大的灵活性和模糊关系的详细分析.
- 在MCDM案例研究中,监管和政策障碍被确定为最有影响力的因素.
- 与现有方法相比,拟议的方法表现出更好的适应不确定性和输入变化的能力.
结论:
- 开发的相似度措施有效地解决了分析 [公式:见文本] 分数模糊集合的局限性.
- 拟议的决策模型为不确定的环境提供了更准确,可解释和可适应的结果.
- 这项研究有助于推进复杂决策分析中的模糊集合理论应用.
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