An extended ISM and MICMAC method under neutrosophic environment

IF 2.6 Q3 MANAGEMENT
S. M. Zanjirchi, Najmeh Faregh
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引用次数: 0

Abstract

PurposeISM technique is one of the tools of interest in soft operations research. The soft nature of this technique has made inevitable use of indeterminacy theories. The present research attempts to develop ISM technique and MICMAC analysis in a neutrosophic space due to the complexity and uncertainty of the decision-making environment.Design/methodology/approachIn this study, single-valued triangular neutrosophic numbers is used to develop Neutrosophic ISM (NISM) and Neutrosophic MICMAC (NMICMAC). First, the general algorithm of NISM and NMICMAC is provided. In the following, the complete description of NISM steps including level value determination, Factor Leveling Algorithm and NISM digraph algorithm are presented. Finally, a description of the NMICMAC steps is described.FindingsAn illustrative example – supplier selection problem – is given to verify the effectiveness of the proposed method and in the discussion section; the comparison and analysis of different aspects of the NISM with the previous methods are discussed.Originality/valueIn this study, NISM and NMICMAC are presented for the first time, so that each pairwise comparison judgment is provided as single valued triangular neutrosophic numbers. The development of the model is continued until the final stages of calculations with neutrosophic numbers, and only in the final stage the results are crispy presented. In addition, not only the factors of process are leveled, but at each level the factors are lined up and their importance is determined.
中性粒细胞环境下ISM和MICMAC方法的扩展
目的ISM技术是软操作研究中的一种重要工具。这种技术的软性使得不确定性理论的使用成为必然。由于决策环境的复杂性和不确定性,本研究试图在中性空间中开发ISM技术和MICMAC分析。设计/方法/方法在本研究中,单值三角中性粒细胞数用于发展neutrosophic ISM(NISM)和Neutrosopheric MICMAC(NMICMAC)。首先,给出了NISM和NMICMAC的通用算法。在下文中,给出了NISM步骤的完整描述,包括电平值确定、因子均衡算法和NISM有向图算法。最后,对NMICMAC步骤进行了描述。发现在讨论部分,给出了一个说明性的例子——供应商选择问题,以验证所提出方法的有效性;对NISM的不同方面与以前的方法进行了比较和分析。原创性/价值在本研究中,首次提出了NISM和NMICMAC,因此每个成对的比较判断都被提供为单值三角形中性粒细胞数。模型的开发一直持续到中子数计算的最后阶段,只有在最后阶段,结果才会清晰呈现。此外,不仅对过程中的因素进行了分级,而且在每个级别上都对因素进行了排列,并确定了它们的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.50
自引率
3.20%
发文量
30
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