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A new approach for evaluating agility in supply chains using Fuzzy Association Rules Mining

机译:基于模糊关联规则挖掘的供应链敏捷性评估新方法

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Besides its effectiveness, supply chain management (SCM) is a complex process because of the stochastic and dynamic nature, multi-criterion and ever-increasing complexity of supply chains. Furthermore, companies have realized that agility is essential for their survival and competitiveness. Consequently, there is no generally accepted method by researchers and practitioners for designing, operating and evaluating agile supply chains. Moreover, the ability to build agile supply chain has developed more slowly than anticipated, because technology for managing agile supply chain is still being developed. Therefore, in this paper, we develop a new approach based on Fuzzy Association Rule Mining to support the decision makers by enhancing the flexibility in making decisions for evaluating agility with both tangibles and intangibles attributes/criteria such as Flexibility, Profitability, Quality, Innovativeness, Pro-activity, Speed of response, Cost and Robustness. Also, by checking the fuzzy classification rules, the goal of knowledge acquisition can be achieved in a framework in which evaluation of agility could be established without constraints, and consequently checked and compared in several details. Efficacy and intricacy of the proposed approach for finding fuzzy association rules from the database for evaluating agility is demonstrated with the help of a numerical example.
机译:除了其有效性之外,由于供应链的随机性和动态性,多准则和不断增加的复杂性,供应链管理(SCM)是一个复杂的过程。此外,公司已经意识到敏捷对于他们的生存和竞争力至关重要。因此,研究人员和从业人员没有普遍接受的用于设计,操作和评估敏捷供应链的方法。此外,由于仍在开发用于管理敏捷供应链的技术,因此建立敏捷供应链的能力的发展速度比预期的要慢。因此,在本文中,我们开发了一种基于模糊关联规则挖掘的新方法,以通过增强决策的灵活性来支持决策者,这些决策可以同时评估有形和无形属性/标准(如灵活性,获利能力,质量,创新性,主动,响应速度,成本和健壮性。而且,通过检查模糊分类规则,可以在一个框架中建立知识的评估而不受限制,并在几个细节上进行检查和比较,从而实现知识获取的目标。借助数值示例,证明了所提出的从数据库中找到模糊关联规则以评估敏捷性的方法的有效性和复杂性。

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