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Cold Chain Logistics Management of Medicine with an Integrated Multi-Criteria Decision-Making Method

机译:集成多准则决策方法的医药冷链物流管理

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摘要

Medicine is the main means to reduce cancer mortality. However, some medicines face various risks during transportation and storage due to the particularity of medicines, which must be kept at a low temperature to ensure their quality. In this regard, it is of great significance to evaluate and select drug cold chain logistics suppliers from different perspectives to ensure the quality of medicines and reduce the risks of transportation and storage. To solve such a multiple criteria decision-making (MCDM) problem, this paper proposes an integrated model based on the combination of the SWARA (stepwise weight assessment ratio analysis) and CoCoSo (combined compromise solution) methods under the probabilistic linguistic environment. An adjustment coefficient is introduced to the SWARA method to derive criteria weights, and an improved CoCoSo method is proposed to determine the ranking of alternatives. The two methods are extended to the probabilistic linguistic environment to enhance the applicability of the two methods. A case study on the selection of drug cold chain logistics suppliers is presented to demonstrate the applicability of the proposed integrated MCDM model. The advantages of the proposed methods are highlighted through comparative analyses.
机译:医学是降低癌症死亡率的主要手段。然而,由于药物的特殊性,某些药物在运输和存储过程中面临着各种风险,必须将其保持在低温下以确保其质量。因此,从不同角度评估和选择药品冷链物流供应商,对于保证药品质量,降低运输和储存风险具有重要意义。为了解决这样的多准则决策问题,本文提出了一种在概率语言环境下基于SWARA(逐步权重评估比率分析)和CoCoSo(综合折衷解决方案)方法相结合的集成模型。将调整系数引入SWARA方法以得出标准权重,并提出一种改进的CoCoSo方法来确定替代方案的排名。将这两种方法扩展到概率语言环境,以增强这两种方法的适用性。提出了一个关于药品冷链物流供应商选择的案例研究,以证明所提出的集成MCDM模型的适用性。通过比较分析突出了所提出方法的优点。

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