基于模糊认知图的复杂系统风险评估:生物制药行业案例

IF 1.7 4区 工程技术 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Complexity Pub Date : 2024-06-30 DOI:10.1155/2024/4369401
Hadi Abbasian, Reza Yousefi-Zenouz, Abdollah Amirkhani, Masoud Shirzadeh, Akbar Abdollahiasl, Shekoufeh Nikfar, Mohammadreza Siahi-Shadabad, Abbas Kebriaeezadeh
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引用次数: 0

摘要

由于生物制药供应链(SC)的复杂性、各种风险的存在以及系统的动态性,分析生物制药供应链具有挑战性。本文提出了一个基于因果关系和模糊认知图(FCM)的框架,用于评估伊朗生物制药公司的供应链风险。我们首先采访了几位生物制药供应专家,以了解潜在的 SC 风险、FCM 概念之间的因果关系、FCM 结构和 FCM 激活周期。最关键、最相关的风险和供应链的重要元素,如成本、时间和质量,被确定为相关的 FCM 概念。然后,我们使用失效模式与效应分析(FMEA)和 SC 风险的 FCM 来评估生物制药 SC 风险对彼此以及 SC 关键要素的影响。然后应用希比安学习算法来训练 FCM 模型。我们测试了不同的情景,以评估 FCM 概念对 SC 风险的影响。所提出的方法可以对风险因素进行优先排序,更重要的是,可以预测和分析每个风险因素/风险组对其他风险或给定风险结果的影响。拟议的供应链管理特征以及通过评估这些特征获得的知识可为制药公司提供实用和有用的信息,以更有效地处理其供应风险。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Risk Assessment for Complex Systems Based on Fuzzy Cognitive Maps: A Case of the Biopharmaceutical Industry

Analyzing the supply chain (SC) of biopharmaceutical drugs can be challenging due to their complexity, the existence of a wide variety of risks, and the dynamics of the system. This paper presents a framework for evaluating the SC risks of Iranian biopharmaceutical companies based on cause-and-effect relationships and fuzzy cognitive maps (FCMs). We first interviewed several biopharmaceutical supply experts to learn about potential SC risks, causal relationships among FCM concepts, FCM structure, and FCM activation cycle. The most critical and relevant risks and significant elements of the SCs, such as cost, time, and quality, were identified as relevant FCM concepts. Then, we used failure mode and effects analysis (FMEA) and the FCM of the SC risks to assess the impacts of the biopharmaceutical SC risks on each other and on the crucial elements of the SCs. The Hebbian learning algorithms were then applied to train the FCM models. We tested different scenarios to evaluate the impacts of FCM concepts on the SC risks. The proposed approach can prioritize risk factors and, more importantly, predict and analyze the effect of each risk factor/risk group on other risks or the outcome of a given risk. The proposed FCM features and the knowledge gained from evaluating them can provide practical and helpful information to pharmaceutical companies to deal with their supply risks more efficiently.

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来源期刊
Complexity
Complexity 综合性期刊-数学跨学科应用
CiteScore
5.80
自引率
4.30%
发文量
595
审稿时长
>12 weeks
期刊介绍: Complexity is a cross-disciplinary journal focusing on the rapidly expanding science of complex adaptive systems. The purpose of the journal is to advance the science of complexity. Articles may deal with such methodological themes as chaos, genetic algorithms, cellular automata, neural networks, and evolutionary game theory. Papers treating applications in any area of natural science or human endeavor are welcome, and especially encouraged are papers integrating conceptual themes and applications that cross traditional disciplinary boundaries. Complexity is not meant to serve as a forum for speculation and vague analogies between words like “chaos,” “self-organization,” and “emergence” that are often used in completely different ways in science and in daily life.
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