Purpose

Forecasting demand of emergency supplies under major epidemics plays a vital role in improving rescue efficiency. Few studies have combined intuitionistic fuzzy set with grey-Markov method and applied it to the prediction of emergency supplies demand. Therefore, this article aims to establish a novel method for emergency supplies demand forecasting under major epidemics.

Design/methodology/approach

Emergency supplies demand is correlated with the number of infected cases in need of relief services. First, a novel method called the Intuitionistic Fuzzy TPGM(1,1)-Markov Method (IFTPGMM) is proposed, and it is utilized for the purpose of forecasting the number of people. Then, the prediction of demand for emergency supplies is calculated using a method based on the safety inventory theory, according to numbers predicted by IFTPGMM. Finally, to demonstrate the effectiveness of the proposed method, a comparative analysis is conducted between IFTPGMM and four other methods.

Findings

The results show that IFTPGMM demonstrates superior predictive performance compared to four other methods. The integration of the grey method and intuitionistic fuzzy set has been shown to effectively handle uncertain information and enhance the accuracy of predictions.

Originality/value

The main contribution of this article is to propose a novel method for emergency supplies demand forecasting under major epidemics. The benefits of utilizing the grey method for handling small sample sizes and intuitionistic fuzzy set for handling uncertain information are considered in this proposed method. This method not only enhances existing grey method but also expands the methodologies used for forecasting demand for emergency supplies.

Highlights (for review)

1. An intuitionistic fuzzy TPGM(1,1)-Markov method (IFTPGMM) is proposed.

2. The safety inventory theory is combined with IFTPGMM to construct a prediction method.

3. Asymptomatic infected cases are taken to forecast the demand for emergency supplies.

中文翻译：

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直观模糊灰色马尔可夫方法在重大疫情应急物资需求预测中的应用

目的

重大疫情下应急物资需求预测对于提高救援效率具有至关重要的作用。很少有研究将直觉模糊集与灰色马尔可夫方法结合起来应用于应急物资需求的预测。因此，本文旨在建立一种重大疫情下应急物资需求预测的新方法。

设计/方法论/途径

紧急物资需求与需要救援服务的感染病例数量相关。首先，提出了一种称为直觉模糊TPGM(1,1)-马尔可夫方法(IFTPGMM)的新方法，并将其用于预测人数的目的。然后，根据IFTPGMM的预测数据，采用基于安全库存理论的方法计算应急物资需求预测。最后，为了证明所提方法的有效性，对 IFTPGMM 与其他四种方法进行了比较分析。

发现

结果表明，与其他四种方法相比，IFPGMM 表现出卓越的预测性能。灰色方法与直觉模糊集的结合已被证明可以有效处理不确定信息并提高预测的准确性。

原创性/价值

本文的主要贡献是提出了一种重大疫情下应急物资需求预测的新方法。该方法考虑了利用灰色方法处理小样本量和利用直观模糊集处理不确定信息的好处。该方法不仅增强了现有的灰色方法，而且扩展了用于预测紧急物资需求的方法。

亮点（供审查）

1. 提出了一种直观模糊TPGM(1,1)-马尔可夫方法(IFTPGMM)。

2. 将安全库存理论与IFPGMM相结合，构建了预测方法。

3. 通过无症状感染者预测应急物资需求。