Computational Optimisation and Learning (COL) Lab, School of Computer Science, University of Nottingham, UK.
Faculty of Transport and Traffic Engineering, University of Belgrade, Serbia.
Waste Manag Res. 2020 Jun;38(6):660-672. doi: 10.1177/0734242X19899729. Epub 2020 Jan 23.
As the number of end-of-life vehicles (ELVs) increases rapidly, their management has become one of the most important environmental topics worldwide. This study is conducted to evaluate various alternatives for location selection of an authorized dismantling center (ADC) for ELVs using a multi-criteria decision-making (MCDM) approach. An intuitionistic fuzzy MCDM-based combinative distance-based assessment (CODAS) approach is proposed to aid waste managers and solve their problem. The intuitionistic fuzzy weighted averaging operator is utilized to aggregate individual opinions of decision-makers into a group opinion. The intuitionistic fuzzy Euclidean and Hamming distances are used to calculate the assessment score of alternatives. A real-life case study of Istanbul is provided to illustrate how this novel intuitionistic fuzzy MCDM-based CODAS approach can be used for alternative selection in real-world applications. The comparison with the available state-of-the-art intuitionistic fuzzy set-based MCDM approaches approves the validity and consistency of the proposed intuitionistic fuzzy CODAS approach. The intuitionistic fuzzy CODAS, WASPAS, and TOPSIS approaches generate exactly the same ordering of alternatives for the new ADC in Istanbul. The results show that the intuitionistic fuzzy CODAS approach indicates valid results and is an effective decision-making technique for vagueness and uncertainty nature of linguistic assessments.
随着报废车辆 (ELV) 的数量迅速增加,其管理已成为全球最重要的环境议题之一。本研究旨在使用多准则决策 (MCDM) 方法评估各种替代方案,以选择授权拆解中心 (ADC) 的位置。提出了一种基于直觉模糊多准则决策的组合贴近度评估 (CODAS) 方法,以帮助废物管理者解决他们的问题。直觉模糊加权平均值算子用于将决策者的个人意见聚合为集体意见。直觉模糊欧几里得和汉明距离用于计算替代方案的评估得分。提供了伊斯坦布尔的实际案例研究,以说明如何在实际应用中使用这种新颖的基于直觉模糊多准则决策的 CODAS 方法进行替代方案选择。与现有的基于最先进的直觉模糊集的 MCDM 方法进行比较,证明了所提出的直觉模糊 CODAS 方法的有效性和一致性。直觉模糊 CODAS、WASPAS 和 TOPSIS 方法为伊斯坦布尔的新 ADC 生成了完全相同的替代方案排序。结果表明,直觉模糊 CODAS 方法提供了有效的结果,并且是一种用于语言评估的模糊性和不确定性的有效决策技术。