Supply Chain Impact Modelling – Simulation and Machine Learning approach

Mohamed Shayeez, V. V. Panicker
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引用次数: 1

Abstract

An epidemic outbreak can cause huge impact not only on human lives alone but also on other sectors relying on it. Supply chain operations are also largely affected from these outbreaks. From the recent epidemic outbreak, severe disruptions affecting both the supply and demand of supply chains were observed. Supply chains being optmized for maximum profits, reduced inventories were less immune to epidemic outbreaks. As a result these firms were left with huge losses during the recent outbreak. This has forced executives to adopt resilience factors to their supply chains. Thus for redesign of supply chains, executives required clear knowledge of how impacts were going to affect their firms. In this paper, simulation modelling for impact analysis of supply chains during an epidemic outbreak is illustrated. This provided a detailed quantitative overview of the impact for executives. Also simulation results were further processed to generate datasets suitable for developing decision support tools using various machine learning algorithms.
供应链影响建模-模拟和机器学习方法
疫情爆发不仅会对人类生命造成巨大影响,还会对依赖疫情的其他部门造成巨大影响。供应链运营也在很大程度上受到这些疫情的影响。从最近的疫情爆发来看,供应链的供应和需求都受到严重干扰。为了实现利润最大化而优化供应链,减少库存对流行病爆发的免疫力较低。结果,这些公司在最近的疫情中蒙受了巨大损失。这迫使高管们在供应链中采用弹性因素。因此,为了重新设计供应链,高管们需要清楚地了解这些影响将如何影响他们的公司。本文阐述了疫情爆发期间供应链影响分析的仿真模型。这为执行人员提供了对影响的详细定量概述。此外,模拟结果进一步处理,以生成适合使用各种机器学习算法开发决策支持工具的数据集。
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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