基于知识的全球供应链操作风险管理智能决策支持系统的开发

IF 16.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Yang-Byung Park, Sung-Joon Yoon, Jun-Su Yoo
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引用次数: 10

摘要

本文提出了一种基于知识的全球供应链操作风险管理智能决策支持系统(DSSRMG),这是一种文献中尚未涉及的全阶段系统。DSSRMG使用结合粒子群优化的增强型人工神经网络预测供应链绩效,使用基于主成分分析的方法推断核心风险源,并使用结合主成分分析的有向图矩阵方法评估风险缓解方案。提出了一种基于自适应网络的模糊推理系统构建缓解方案知识库的方法。最后用一个工业实例说明了DSSRMG的性能。计算实验表明,DSSRMG所采用的技术是很好的。特别是对有用的操作指标选择算法,性能预测准确率平均提高了7.1%。DSSRMG为供应链管理者准确预测和有效控制运营风险提供了实用的工具。[收稿日期:2017年3月9日;修订日期:2017年7月22日;录用日期:2017年10月2日]
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of a knowledge-based intelligent decision support system for operational risk management of global supply chains
This paper proposes a knowledge-based intelligent decision support system for operational risk management of global supply chains (DSSRMG), a full-phase system not yet treated in the literature. DSSRMG predicts the supply chain performance using the enhanced artificial neural network combined with particle swarm optimisation, infers the core risk source using a method based on principle component analysis, and evaluates risk mitigation alternatives using the digraph-matrix approach combined with principle component analysis. A methodology using an adaptive-network-based fuzzy inference system is suggested to construct the knowledge base for mitigation alternatives. An industrial example is used to illustrate the performance of DSSRMG. Computational experiments show that the techniques used for DSSRMG are excellent. Especially, the algorithm for selecting the useful operation indicators improves the performance prediction accuracy by 7.1% on average. DSSRMG provides supply chain managers with a practical tool to accurately predict and effectively control the operational risk. [Received: 9 March 2017; Revised: 22 July 2017; Accepted: 2 October 2017]
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来源期刊
Accounts of Chemical Research
Accounts of Chemical Research 化学-化学综合
CiteScore
31.40
自引率
1.10%
发文量
312
审稿时长
2 months
期刊介绍: Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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