库存问题和参数度量 $m_λ$

Irina Georgescu
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引用次数: 0

摘要

可信度理论由 B. Liu 提出,是描述模糊不确定性的一种新方法。可信度度量是可信度理论的基本概念。最近,L.Yang 和 K. Iwamura 通过定义参数度量 $m_{\lambda}$($\lambda$ 是区间 $[0,1]$ 中的实参数,对于 $\lambda=1/2$,我们得到了可信度量的特殊概念)扩展了可信度量。通过使用 $m_{\lambda}$ 度量,我们在本文中研究了一个风险中性的多项目库存问题。我们的构造概括了李一和刘一在 2019 年提出的可信库存模型。在我们的模型中,需求向量的分量是模糊变量,最大化问题通过使用 $m_{\lambda}$ 预期值的概念来表述。我们将证明优化问题求解的一般公式,并从中获得计算需求为梯形模糊数和三角形模糊数的特殊情况下最优解的有效公式。对于$\lambda=1/2$,我们得到了李和刘的可信库存问题最优解的计算公式。这些计算公式适用于从数字数据中得到的一些 $m_{\lambda}$ 模型。
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Inventory problems and the parametric measure $m_λ$
The credibility theory was introduced by B. Liu as a new way to describe the fuzzy uncertainty. The credibility measure is the fundamental notion of the credibility theory. Recently, L.Yang and K. Iwamura extended the credibility measure by defining the parametric measure $m_{\lambda}$ ($\lambda$ is a real parameter in the interval $[0,1]$ and for $\lambda= 1/2$ we obtain as a particular case the notion of credibility measure). By using the $m_{\lambda}$-measure, we studied in this paper a risk neutral multi-item inventory problem. Our construction generalizes the credibilistic inventory model developed by Y. Li and Y. Liu in 2019. In our model, the components of demand vector are fuzzy variables and the maximization problem is formulated by using the notion of $m_{\lambda}$-expected value. We shall prove a general formula for the solution of optimization problem, from which we obtained effective formulas for computing the optimal solutions in the particular cases where the demands are trapezoidal and triangular fuzzy numbers. For $\lambda=1/2$ we obtain as a particular case the computation formulas of the optimal solutions of the credibilistic inventory problem of Li and Liu. These computation formulas are applied for some $m_{\lambda}$-models obtained from numerical data.
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