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Facilitating uncertainty treatment in the risk assessment of container supply chains

机译:促进集装箱供应链风险评估中的不确定性处理

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摘要

Over the last few years there has been a growing international recognition that Container Supply Chains (CSCs) contribute to economic prosperity. But they are uniquely vulnerable to many risks caused by both the traditional hazards, such as physical breaches in the integrity of shipments and the newly rising threats associated with pirate and terrorist attacks. To allow better understanding and control of the risks, it is necessary for the stakeholders to proactively assess the chains' security and safety in advance, or reactively discover risks after a detrimental event occurs.rnThis paper explores the various CSC risks, identifies common themes, and deals with the corresponding uncertainties by developing two novel risk modelling methods. One is to develop a fuzzy evidential reasoning approach for carrying out the security estimation of a vulnerable port system against terrorism attacks and the other is to produce a Bayesian network decision support tool for identifying vulnerable assets in a port security protection scenario. Consequently, the methods can be used to assemble and process subjective risk information on different aspects of a container transport system from multiple experts in a systematic way. Outcomes of the models can also provide decision makers with a transparent tool to evaluate CSC safety and security policy options for a specific scenario in a cost-effective manner
机译:在过去的几年中,国际上越来越认识到集装箱供应链(CSC)有助于经济繁荣。但是,它们极易受到传统危险造成的许多风险的影响,例如传统的运输完整性破坏以及与海盗和恐怖袭击有关的新威胁。为了更好地理解和控制风险,利益相关者有必要事先主动评估链的安全性,或者在有害事件发生后以反应方式发现风险。本文探讨了各种CSC风险,确定了共同主题,通过开发两种新颖的风险建模方法来处理相应的不确定性。一种是开发一种模糊证据推理方法,以对易受攻击的港口系统进行安全评估,以防止恐怖主义攻击;另一种是,开发一种贝叶斯网络决策支持工具,用于在端口安全保护方案中识别易受攻击的资产。因此,该方法可用于以系统的方式从多位专家那里收集和处理关于集装箱运输系统不同方面的主观风险信息。模型的结果还可以为决策者提供一种透明的工具,以经济高效的方式评估特定情况下的CSC安全和安保策略选项

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    ZL Yang; S Bonsall; J Wang;

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    Liverpool Logistics, Offshore and Marine (LOOM) Research Centre, Liverpool John Moores University, Liverpool, UK;

    rnLiverpool Logistics, Offshore and Marine (LOOM) Research Centre, Liverpool John Moores University, Liverpool, UK;

    rnLiverpool Logistics, Offshore and Marine (LOOM) Research Centre, Liverpool John Moores University, Liverpool, UK;

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