基于 OWA 距离的低碳供应链绿色供应商评价与选择的单值 Neutrosophic 语言 TOPSIS 方法。
An OWA Distance-Based, Single-Valued Neutrosophic Linguistic TOPSIS Approach for Green Supplier Evaluation and Selection in Low-Carbon Supply Chains.
机构信息
College of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou 310018, China.
School of Business, Ningbo University, Ningbo 315211, China.
出版信息
Int J Environ Res Public Health. 2018 Jul 8;15(7):1439. doi: 10.3390/ijerph15071439.
This paper presents a technique based on the ordered weighted averaging (OWA) distance for the single-valued neutrosophic linguistic (SVNL) technique for order preference by similarity to an ideal solution (TOPSIS). First, the inadequacies of the existing SVNL TOPSIS are analyzed in detail. Second, a SVNL OWA distance (SVNLOWAD) measure is presented, and based on this, a modified TOPSIS, termed the SVNLOWAD-TOPSIS, is developed for multiple attribute decision-making problems with SVNL information. Third, a revised relative coefficient is proposed to rank potential alternatives. Finally, a numerical example concerning green supplier selection in low-carbon supply chains is introduced to demonstrate the effectiveness of the model.
本文提出了一种基于有序加权平均（OWA）距离的单值 neutrosophic 语言（SVNL）技术，用于相似度偏好的顺序偏好接近理想解（TOPSIS）。首先，详细分析了现有 SVNL TOPSIS 的不足。其次，提出了一种 SVNL OWA 距离（SVNLOWAD）度量，并在此基础上，为具有 SVNL 信息的多属性决策问题开发了一种改进的 TOPSIS，称为 SVNLOWAD-TOPSIS。第三，提出了一个修正的相对系数来对潜在的替代方案进行排序。最后，引入了一个低碳供应链中绿色供应商选择的数值示例，以验证模型的有效性。
Zotero 插件