通过使用复杂的图片模糊软集来优化建筑供应链管理的多属性决策方法
Ali Asghar1, Khuram A Khan1, Marwan A Albahar2
1Department of Mathematics, University of Sargodha, Sargodha, Sargodha, Pakistan.
PeerJ. Computer science
|September 14, 2023
概括
本研究引入了一个复杂的图片模糊软集 (cpFSS) 来处理供应商选择中的不确定性. 新方法提供了一种更灵活,更可靠的方法,在复杂的决策场景中选择最佳供应商.
科学领域:
- 决策科学 决策科学
- 模糊的集合理论 模糊的集合理论
- 运营研究 运营研究
背景情况:
- 供应商选择对于组织的成功至关重要,但由于固有的不确定性而复杂化.
- 现有的多标准决策分析和模糊逻辑方法与复杂的不确定性作斗争.
- 需要一种新的方法来有效地管理供应商选择中的模糊性和基于信息的不确定性.
研究的目的:
- 开发一个通用的模糊集结构,复杂图片模糊软集 (cpFSS),以解决供应商选择中的基于信息的不确定性.
- 在cpFSS中引入振幅和相位术语,用于管理模糊的成员和周期性.
- 让决策者能够将中立的意见纳入评估过程.
主要方法:
- 对cpFSS概念和集合理论运算的研究,用说明性的例子.
- 开发一种使用cpFSS矩阵集成的多属性决策 (MADM) 算法 (核心矩阵,决策值矩阵,得分).
- 在现实建筑项目供应商选择案例中实施拟议的算法.
主要成果:
- cpFSS结构有效地处理基于信息的不确定性和周期性.
- 拟议的MADM算法使用cpFSS,提供一致的供应商排名.
- 使用毕达哥拉斯方法的灵敏度分析证实了结果的稳定性.
结论:
- 复杂图像模糊软集 (cpFSS) 与现有的模糊集结构相比,为不确定性下的决策提供了更灵活和可靠的框架.
- 开发的MADM算法对现实世界供应商选择问题是有效的,确保一致和可靠的结果.
- cpFSS方法通过适应中立意见和管理复杂的不确定性来增强决策.
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