Mishra Arunodaya Raj, Saha Abhijit, Rani Pratibha, Pamucar Dragan, Dutta Debjit, Hezam Ibrahim M
Department of Mathematics, Government College Raigaon, Satna, MP 485441 India.
Department of Mathematics, Techno College of Engineering Agartala, Maheshkhola, Tripura, 799004 India.
Soft comput. 2022;26(17):8821-8840. doi: 10.1007/s00500-022-07192-8. Epub 2022 Jun 3.
The assessment of sustainable supplier is very significant for supply chain management (SCM). The procedure of sustainable supplier selection (SSS) is a complex process for decision experts (DEs) due to the association of diverse qualitative and quantitative attributes. As the uncertainty is usually ensued in the SSS and hesitant fuzzy set (HFS), an extension of fuzzy set (FS) has been demonstrated as one of the effective ways to treat the uncertain information in realistic problems. The objective of this paper is to propose an integrated hesitant fuzzy-data envelopment analysis (DEA)-full consistency method (FOCUM)-multi attribute border approximation area comparison (MABAC) method called HF-DEA-FUCOM-MABAC framework to assess the multi-attribute decision-making (MADM) problems on HFSs settings. In this line, first, the efficient alternatives are chosen using the DEA method. Second, The FUCOM is used to compute the subjective weight of attributes. Third, The HF-MABAC method is presented to prioritize the alternatives in an MADM problem. In the following, a case study of SSS problem for an Auto-making company is taken to show the practicality and utility of the presented approach. Next, we present a sensitivity investigation with different attribute weights set to observe the steadiness of the presented approach. Finally, we draw attention toward a comparison between presented approach with the extant HF-FOCUM-TOPSIS model to show its advantage and potency as well.
可持续供应商评估对于供应链管理（SCM）而言非常重要。由于多种定性和定量属性相互关联，可持续供应商选择（SSS）过程对于决策专家（DEs）来说是一个复杂的过程。由于SSS中通常会出现不确定性，而犹豫模糊集（HFS）是模糊集（FS）的一种扩展，已被证明是处理现实问题中不确定信息的有效方法之一。本文的目的是提出一种集成的犹豫模糊数据包络分析（DEA）-完全一致性方法（FOCUM）-多属性边界近似区域比较（MABAC）方法，即HF-DEA-FUCOM-MABAC框架，以评估犹豫模糊集环境下的多属性决策（MADM）问题。为此，首先，使用DEA方法选择有效备选方案。其次，使用FUCOM计算属性的主观权重。第三，提出HF-MABAC方法对MADM问题中的备选方案进行排序。接下来，以一家汽车制造公司的SSS问题为例，展示所提出方法的实用性和有效性。然后，我们进行了不同属性权重设置的敏感性研究，以观察所提出方法的稳定性。最后，我们将所提出的方法与现有的HF-FOCUM-TOPSIS模型进行比较，以展示其优势和效能。
