Alrasheedi Adel Fahad, Rani Pratibha, Mishra Arunodaya Raj, Alshamrani Ahmad M, Cavallaro Fausto
Statistics and Operations Research Department, College of Science, King Saud University, 11451, Riyadh, Saudi Arabia.
Faculty of Business and Communications, INTI International University, 71800, Nilai, Negeri Sembilan, Malaysia.
Sci Rep. 2024 Nov 9;14(1):27373. doi: 10.1038/s41598-024-78284-8.
The present work proposes a new decision support tool for assessing the sustainable suppliers in the healthcare supply chain. For this purpose, the classical Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) model is integrated with the Sugeno-Weber weighted averaging operators, modified symmetry point of criterion (SPC) model, rank sum (RS) tool and Fermatean fuzzy sets (FFSs), and named as the 'FF-SPC-RS-MARCOS' framework. The developed model firstly determines the decision experts' weights through RS model. Second, novel Sugeno-Weber weighted operators are introduced to combine the experts' opinions. Third, a unified weighting procedure is presented based on the combination of modified SPC approach for objective weight and RS method for subjective weight of attributes. To this aim, a novel distance measure is introduced for FFSs and further applied to compute the distance between aggregated Fermatean fuzzy numbers and symmetry point value of an attribute in the modified SPC approach. Further, a hybrid FF-SPC-RS-MARCOS approach is proposed to tackle the decision-making problems on FFSs setting. To elucidate the efficacy of the developed method, it is applied to a case study of sustainable supplier selection problem in the healthcare supply chain. The paper further conducts sensitivity investigation and comparison with existent approaches to test the stability and robustness of the ranking outcomes. This study shows how the proposed MARCOS method in combination with SPC and RS models can be used to prioritize the alternative suppliers in the healthcare supply chain. The introduced work provides a new methodology, which can help the practitioners and academics to evaluate suppliers with uncertain information and can also be employed to other areas facing similar types of decision-making problems.
本研究提出了一种用于评估医疗供应链中可持续供应商的新型决策支持工具。为此，将经典的基于折衷解的替代方案测量与排序（MARCOS）模型与Sugeno-Weber加权平均算子、改进的准则对称点（SPC）模型、秩和（RS）工具以及费马模糊集（FFS）相结合，并命名为“FF-SPC-RS-MARCOS”框架。所开发的模型首先通过RS模型确定决策专家的权重。其次，引入新颖的Sugeno-Weber加权算子来组合专家意见。第三，基于改进的SPC方法确定属性客观权重和RS方法确定属性主观权重相结合的方式，提出了一种统一的加权程序。为此，为FFS引入了一种新颖的距离度量，并进一步应用于计算修正SPC方法中聚合费马模糊数与属性对称点值之间的距离。此外，还提出了一种混合的FF-SPC-RS-MARCOS方法来解决FFS环境下的决策问题。为了阐明所开发方法的有效性，将其应用于医疗供应链中可持续供应商选择问题的案例研究。本文还进行了敏感性调查，并与现有方法进行比较，以测试排序结果的稳定性和鲁棒性。本研究展示了所提出的MARCOS方法与SPC和RS模型相结合如何用于对医疗供应链中的替代供应商进行优先级排序。所介绍的工作提供了一种新的方法，可帮助从业者和学者利用不确定信息评估供应商，也可应用于面临类似决策问题的其他领域。
