中性聚合运算符及其在软件选址选址中的应用.
Sumbal Ali1, Muhammad Rahim1, Sanaa A Bajri2
1Department of Mathematics and Statistics, Hazara University, Mansehra, 21300, KPK, Pakistan.
Heliyon
|June 3, 2024
概括
这项研究引入了一种新的中性学集合 (NS) 框架,用于管理成员在决策中的影响程度. 新模型增强了聚合运营商,用于改进多重标准决策 (MCDM) 应用程序.
科学领域:
- 决策科学 决策科学
- 信息科学 信息科学 信息科学
- 数学 数学 是一个数学.
背景情况:
- 传统的中性学集合 (NS) 在聚合过程中难以管理成员程度的影响.
- 现有的模型缺乏强大的机制来平衡会员程度 (MD),不确定性会员程度 (IMD) 和非会员程度 (NMD).
研究的目的:
- 通过引入中性质集合 (NS) 来扩展中性质集合的概念.
- 开发一种新的多重标准决策 (MCDM) 模型,使用特定参数有效处理MD,IMD和NMD的影响.
- 引入新的聚合运算符来组合中性信息.
主要方法:
- 介绍了具有定义的运行规律的中性质集合 (NS).
- 开发一系列适用于中性信息的聚合运算符 (AO).
- 制定一个新的MCDM模型,利用拟议的AOs.
主要成果:
- 拟议的NS框架有效地管理了会员,不确定性和非会员程度的影响.
- 一个关于软件办公室位置选择的案例研究表明了新的MCDM模型的实际适用性和有效性.
- 开发的聚合运算符成功地将中性学信息结合起来,用于决策.
结论:
- 引入的中性素学集合和MCDM模型比现有方法提供了显著的进步.
- 该模型的有效性和有效性通过比较分析得到证实,突出了其应对现实生活决策挑战的潜力.
- 这项研究为加强涉及不确定和不准确信息的决策过程提供了一个强大的框架.
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