基于尺度变换的BWM改进方法及其对电网关键物资筛选的应用
Improved BWM Method Based on Scale Transformation and Its Application in Selecting Key Materials for Power Grid
DOI: 10.12677/aam.2025.143129, PDF,    国家社会科学基金支持
作者: 张 勇:国网江苏省电力有限公司物资分公司,江苏 南京;王 超:东南大学网络空间安全学院,江苏 南京;东南大学教育部计算机网络和信息集成重点实验室,江苏 南京;仲 翔, 王月虎:南京财经大学管理科学与工程学院,江苏 南京
关键词: 尺度变换非线性BWM国家电网物资选择区间分析Scale Transformation Nonlinear BWM State Grid Corporation of China Material Selection Interval Analysis
摘要: 区间分析法是处理非线性最优最劣法(BWM)存在多解问题的有效方法。本文基于权重区间中心点的大小关系,提出了一种无需计算区间优先度即可获得优先度矩阵的全新便捷算法;然后,在此基础之上,利用“尺度变换”的思想,给出了几类求解权重区间中心点的估计方法,并探讨了这些方法的计算偏差;最后,利用本文所提方法研究了一类电网关键物资的选取问题。本研究简化了已有文献中的区间分析法,规避了求解非线性优化模型的复杂计算过程,推广了非线性BWM的应用范围。
Abstract: Interval analysis is an effective method for dealing with the existence of multiple solutions in nonlinear Best-Worst Methods (BWM). This article proposes a convenient algorithm for obtaining the priority matrix without calculating the interval priority based on the size relationship of the center points of the weight interval. Then, based on this, several methods for estimating the center point of the weight interval were proposed using the idea of “scale transformation”, and the calculation bias of these methods was discussed. Finally, the method proposed in this article was used to study the selection of key materials for a class of power grid enterprises. This study greatly simplifies the interval analysis method in existing literature, and avoids the complex calculation process of solving nonlinear optimization models, and extends the application scope of nonlinear BWM.
文章引用:张勇, 王超, 仲翔, 王月虎. 基于尺度变换的BWM改进方法及其对电网关键物资筛选的应用[J]. 应用数学进展, 2025, 14(3): 422-435. https://doi.org/10.12677/aam.2025.143129

参考文献

[1] Saaty, T.L. (1977) A Scaling Method for Priorities in Hierarchical Structures. Journal of Mathematical Psychology, 15, 234-281. [Google Scholar] [CrossRef
[2] Arora, A., Jain, J., Gupta, S. and Sharma, A. (2020) Identifying Sustainability Drivers in Higher Education through Fuzzy Ahp. Higher Education, Skills and Work-Based Learning, 11, 823-836. [Google Scholar] [CrossRef
[3] Darzi, M.A. (2024) Overcoming Barri-ers to Integrated Management Systems via Developing Guiding Principles Using G-AHP and F-TOPSIS. Expert Sys-tems with Applications, 239, Article ID: 122305. [Google Scholar] [CrossRef
[4] Daimi, S. and Rebai, S. (2023) Sustainability Performance As-sessment of Tunisian Public Transport Companies: AHP and ANP Approaches. Socio-Economic Planning Sciences, 89, Article ID: 101680. [Google Scholar] [CrossRef
[5] Hassanzadeh, M.R. and Valmohammadi, C. (2021) Evaluation and Ranking of the Banks and Financial Institutes Using Fuzzy AHP and TOPSIS Techniques. International Journal of Op-erational Research, 40, 297-317. [Google Scholar] [CrossRef
[6] Rezaei, J. (2015) Best-Worst Multi-Criteria Decision-Making Meth-od. Omega, 53, 49-57. [Google Scholar] [CrossRef
[7] Rezaei, J. (2016) Best-Worst Multi-Criteria Decision-Making Method: Some Properties and a Linear Model. Omega, 64, 126-130. [Google Scholar] [CrossRef
[8] 黄龙山. 基于SVM的电网物资价格预测模型研究[J]. 中国新技术新产品, 2023(17): 142-145.
[9] 程晓晓, 蒲兵舰, 张国平, 等. 基于集成学习的物资采购价格辅助决策方法[J]. 吉林大学学报(信息科学版), 2022, 40(5): 875-883.
[10] 吴天宇. 铁塔企业物资采购价格预测研究[J]. 中小企业管理与科技, 2022(17): 70-72.
[11] 刘达, 刘雨萌, 许晓敏. 基于Copula函数特征筛选的电力物资供应商投标价格预测[J]. 技术经济, 2021, 40(10): 1-9.
[12] 刘欢, 刘苗, 司徒雪颖. 国家电网公司物资招标采购价格统计分析研究[J]. 统计与管理, 2019(6): 87-89.
[13] 靳占新, 徐中一. 大数据背景下物资价格预测方法[J]. 中国电力企业管理, 2018(36): 44-45.
[14] 柴利达, 薛沁文, 毛娜, 等. 基于大数据的物资价格预测方法探索[J]. 电力大数据, 2017, 20(12): 13-20.
[15] 邹筱, 徐俊. 基于不可预测策略的物资采购价格管控模式分析[J]. 现代商贸工业, 2017(18): 25-27.