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A new method for trapezoidal fuzzy numbers ranking based on the Shadow length and its application to manager's risk taking

机译:基于影子长度的梯形模糊数排序新方法及其在经理冒险中的应用

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摘要

Ranking of fuzzy numbers is one of the practicable operators, which plays an important role in fuzzy mathematical, decisions and engineering procedures. There is considerable work in ranking of fuzzy numbers that have been improved over time. However, some strong ranking methods need to calculate complex and lengthy mathematical calculations in their ordering processes. In this paper, we represent a novel ranking method of trapezoidal/triangular fuzzy numbers (TFNs) based on the Shadow length, which is simply coded in any programming language. On the other hand, many fuzzy numbers ranking methods give the same order for fuzzy numbers in any level of manager's risk taking. So we insert the risk taking factor (RF) to order fuzzy numbers and provide a reasonable range of fuzzy numbers comparison through wide levels of this factor. Furthermore, we apply and compare several useful examples and ranking methods to depict the reasonable performance of our proposed method.
机译:模糊数排名是可行的运算符之一,它在模糊数学,决策和工程程序中起着重要作用。随着时间的推移,对模糊数字进行排名的工作量很大。但是,某些强排序方法需要在排序过程中计算复杂而冗长的数学计算。在本文中,我们提出了一种基于阴影长度的梯形/三角形模糊数(TFN)的新颖排序方法,该方法可以用任何编程语言简单地编码。另一方面,在经理人承担风险的任何水平上,许多模糊数排名方法都为模糊数给出了相同的顺序。因此,我们将风险承担因子(RF)插入到模糊数的顺序中,并通过该因子的宽泛程度提供合理范围的模糊数比较。此外,我们应用并比较了几个有用的示例和排序方法,以描述所提出方法的合理性能。

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