一个新的决策支持系统,用于区间值的企业的可持续物流管理
Umar Ali1,2, Junxiang Li1,2, Qin Qi3
1Business School, University of Shanghai for Science and Technology, Shanghai, 200093, China.
Scientific reports
|August 29, 2025
概括
这项研究引入了一种新的决策方法,用于可持续的物流管理,使用间隔值的费尔马图像模糊集 (IVFPFS). 这种方法提高了弹性,并为复杂的后勤挑战提供了现实的解决方案.
科学领域:
- 模糊集合理论
- 运营研究
- 可持续物流管理
背景情况:
- 可持续的物流管理涉及复杂的,不稳定的决策过程.
- 现有的方法与物流固有的不确定和不可靠的数据作斗争.
- 间隔值的费尔玛图像模糊集 (IVFPFS) 为处理此类数据提供了强大的框架.
研究的目的:
- 为可持续物流管理开发一种新的多属性决策 (MADM) 方法.
- 介绍和分析间隔值的费尔马图片模糊爱因斯坦加权平均 (IVFPFEWA) 和几何 (IVFPFEWG) 运算符.
- 在可持续物流中提高决策准确性和现实性.
主要方法:
- 使用间隔值的费尔马图片模糊集 (IVFPFS) 来建模不确定的数据.
- 开发和应用IVFPFEWA和IVFPFEWG聚合运营商.
- 在IVFPFS结构中实施基于爱因斯坦聚合的新MADM方法.
- 进行比较和敏感性分析以验证拟议的方法.
主要成果:
- 拟议的MADM方法有效处理物流中的复杂和不确定的数据.
- 在IVFPFS框架内,IVFPFEWA和IVFPFEWG运营商表现出对汇总的熟练程度.
- 比较和敏感性分析证实了该战略的一致性,效力和实用性.
- 开发的技术为弹性物流系统管理提供了现实的决策.
结论:
- 采用IVFPFS和爱因斯坦运营商的新型MADM方法为可持续物流决策提供了卓越的解决方案.
- 这种方法比传统的管理物流复杂性的策略更现实,更有效.
- 这项研究为提高物流系统的弹性和可持续性提供了有价值的工具.
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