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Resilient Supplier Selection Through Introducing a New Interval-Valued Intuitionistic Fuzzy Evaluation and Decision-Making Framework

机译:通过引入新的区间值直觉模糊评估和决策框架来选择弹性供应商选择

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摘要

Adaptability to change is one of the essential requirements of the supply chain for organizations in a competitive environment. Development of resilience strategies is the key to achieving this goal. Another issue in supply chains is the necessity for a way of dealing with uncertainty. Therefore, fuzzy logic and numbers have been widely used to model the uncertainty in the problems. The purpose of this paper is to facilitate supply chain management by developing a new approach in resilient supplier selection problem. In this study, after gathering the judgment of decision makers (DMs) as linguistic variables and converting them to interval-valued intuitionistic fuzzy (IVIF) numbers, the weight of each criterion is determined based on an entropy index; then, the complex proportional assessment (COPRAS) method based on IVIF numbers is used for ranking the suppliers. Objective and subjective weights are calculated to determine weights of DMs. Finally, due to the advantages of the last aggregation approaches, weights of DMs and COPRAS scores are aggregated by the weighted aggregated sum product assessment method (WASPAS). Finally, the effectiveness of the proposed method is shown by using the method in two case studies from the literature.
机译:改变的适应性是竞争环境中组织供应链的基本要求之一。恢复力战略的发展是实现这一目标的关键。供应链中的另一个问题是处理不确定性的方式的必要性。因此,模糊逻辑和数字已被广泛用于模拟问题的不确定性。本文的目的是通过在弹性供应商选择问题中开发一种新方法来促进供应链管理。在本研究中,在收集决策者(DMS)作为语言变量并将其转换为间隔的直觉模糊(IVIF)数量之后,每个标准的重量基于熵指数确定;然后,基于IVIF数字的复数比例评估(COPRAS)方法用于排名供应商。目标和主观重量计算以确定DMS的重量。最后,由于最后的聚合方法的优点,通过加权聚合和产品评估方法(WASPA)汇总了DMS和Copras分数的权重。最后,通过使用文献的两个案例研究中的方法显示所提出的方法的有效性。

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