Supply Chain Impact Modelling – Simulation and Machine Learning approach

供应链 爆发 计算机科学 弹性(材料科学) 经济影响分析 供应链管理 业务 供应链风险管理 风险分析(工程) 产业组织 运筹学 经济 服务管理 工程类 营销 微观经济学 生物 热力学 物理 病毒学
作者
Mohamed Shayeez,Vinay V. Panicker
出处
期刊:2021 International Conference on System, Computation, Automation and Networking (ICSCAN)
标识
DOI:10.1109/icscan53069.2021.9526484
摘要

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.

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