加强绿色供应商选择:一种非线性编程方法,在立方毕达哥拉斯模糊语境中使用TOPSIS
Musa Khan1, Wu Chao1, Muhammad Rahim2
1School of Finance and Economics, Jiangsu University, Zhenjiang, Jiangsu, P. R. China.
PloS one
|December 5, 2024
概括
本研究引入了一种新的非线性编程方法,使用立方毕达哥拉斯模糊集来选择最好的绿色供应商. 它有效地将先进技术与环境标准相结合,用于智能决策.
科学领域:
- 运营研究 运营研究
- 信息技术 信息技术 信息技术
- 环境管理环境管理
背景情况:
- 人工智能和物联网等信息和通信技术 (ICT) 正在将生产系统转变为智能生产系统.
- 整合ICT与环境标准对于现代供应商选择至关重要.
- 现有的方法很难有效地表示复杂的模糊信息.
研究的目的:
- 为绿色供应商选择开发一种新的非线性编程 (NLP) 方法.
- 为了在决策中使用立方毕达哥拉斯模糊集 (CPFS) 来增强信息表示.
- 为了解决使用间隔值PFS (IVPFS) 和PFS的现有方法的局限性.
主要方法:
- 提出了一个非线性编程 (NLP) 模型.
- 通过与理想解决方案相似的顺序偏好技术 (TOPSIS) 已集成.
- 立方毕达哥拉斯模糊集 (CPFS) 用于处理不确定性和不精确性.
主要成果:
- 拟议的NLP-TOPSIS方法有效地识别了最佳的绿色供应商.
- CPFS成功地整合了区间值的PFS和PFS信息.
- 该方法通过案例研究来证明其准确性和有效性.
结论:
- 这种新的方法为智能环境中的绿色供应商选择提供了一个强大的框架.
- CPFS提供了一种优越的方法来表示复杂的决策信息.
- 这项研究通过先进的决策支持系统,为可持续的供应链管理做出了贡献.
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