Khan Musa, Chao Wu, Rahim Muhammad, Amin Fazli
School of Finance and Economics, Jiangsu University, Zhenjiang, Jiangsu, P. R. China.
Department of Mathematics and Statistics, Hazara University, Mansehra, Khyber Pakhtunkhwa, Pakistan.
PLoS One. 2024 Dec 5;19(12):e0310956. doi: 10.1371/journal.pone.0310956. eCollection 2024.
The advancements in information and communication technologies have given rise to innovative developments such as cloud computing, the Internet of Things, big data analytics, and artificial intelligence. These technologies have been integrated into production systems, transforming them into intelligent systems and significantly impacting the supplier selection process. In recent years, the integration of these cutting-edge technologies with traditional and environmentally conscious criteria has gained considerable attention in supplier selection. This paper introduces a novel Nonlinear Programming (NLP) approach that utilizes the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to identify the most suitable green supplier within cubic Pythagorean fuzzy (CPF) environments. Unlike existing methods that use either interval-valued PFS (IVPFS) or Pythagorean fuzzy sets (PFS) to represent information, our approach employs cubic Pythagorean fuzzy sets (CPFS), effectively addressing both IVPFS and PFS simultaneously. The proposed NLP models leverage interval weights, relative closeness coefficients (RCC), and weighted distance measurements to tackle complex decision-making problems. To illustrate the accuracy and effectiveness of the proposed selection methodology, we present a real-world case study related to green supplier selection.
信息和通信技术的进步催生了云计算、物联网、大数据分析和人工智能等创新发展。这些技术已被集成到生产系统中，将其转变为智能系统，并对供应商选择过程产生了重大影响。近年来，这些前沿技术与传统的环保标准相结合，在供应商选择中受到了相当大的关注。本文介绍了一种新颖的非线性规划（NLP）方法，该方法利用理想解法相似性排序技术（TOPSIS）在立方毕达哥拉斯模糊（CPF）环境中识别最合适的绿色供应商。与现有使用区间值毕达哥拉斯模糊集（IVPFS）或毕达哥拉斯模糊集（PFS）来表示信息的方法不同，我们的方法采用立方毕达哥拉斯模糊集（CPFS），有效地同时解决了IVPFS和PFS问题。所提出的NLP模型利用区间权重、相对贴近度系数（RCC）和加权距离测量来解决复杂的决策问题。为了说明所提出的选择方法的准确性和有效性，我们给出了一个与绿色供应商选择相关的实际案例研究。
