通过使用复杂的毕达哥拉斯模糊粗略WASPAS方法对业务工程问题的可能解决方案的分类
Tahir Mahmood1, Walid Emam2, Jabbar Ahmmad3
1Department of Mathematics and Statistics, International Islamic University, Islamabad, Pakistan. tahirbakhat@iiu.edu.pk.
Scientific reports
|May 13, 2025
概括
本研究介绍了一个复杂的毕达哥拉斯模糊粗略集,以应对复杂性和资源限制等业务工程挑战. 新的框架有助于对复杂的业务问题的解决方案进行分类.
科学领域:
- 商业工程 商业工程
- 信息科学 信息科学 信息科学
- 决策科学 决策科学 决策科学
背景情况:
- 商业工程面临的挑战包括复杂性,快速的技术变化,资源限制和跨学科合作.
- 在解决这些复杂问题时,现有的方法可能会在先进的数据和风险数据丢失方面扎.
- 需要对这些多方面的商业工程问题进行分类解决方案.
研究的目的:
- 开发一种新的数学框架,以应对复杂的商业工程挑战.
- 介绍一个复杂的毕达哥拉斯模糊粗略集,扩展塔米尔的复杂模糊集概念.
- 为实践应用建立聚合运营商和决策技术.
主要方法:
- 一个复杂的毕达哥拉斯模糊粗略集的开发,基于塔米尔的复杂模糊集.
- 使用Yager的t-norm和t-conorm制定基本的运行规律.
- 启动复杂的毕达哥拉斯模糊粗略的雅格加权平均和几何聚合运算符.
- 介绍了WASPAS (权重总和产品评估) 技术用于MADM问题.
主要成果:
- 提出的复杂的毕达哥拉斯模糊粗略集为处理不确定性和复杂性提供了一个强大的方法.
- 为新的集合结构定义了新的聚合运算符 (Yager加权平均和几何运算符).
- 使用新框架的WASPAS技术被证明用于对业务工程解决方案进行分类.
- 一个说明性的例子和比较分析验证了所介绍的理论的有效性和优势.
结论:
- 开发的复杂的毕达哥拉斯模糊粗略集为管理商业工程中的复杂性和不确定性提供了一个强大的工具.
- 新的聚合运算符和WASPAS技术为复杂的商业环境中的决策提供了增强的能力.
- 这项研究为分类关键业务工程挑战的解决方案提供了一种新的方法,改善数据处理和减少数据丢失.
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