基于中智Z数WASPAS的多属性决策方法
Multi-Attribute Decision-Making Method Based on Neutrosophic Z-Number WASPAS
DOI: 10.12677/aam.2025.147352, PDF,    科研立项经费支持
作者: 万国柔：四川建筑职业技术学院基础教学部，四川 德阳；荣 源*：宁夏医科大学创新创业学院，宁夏 银川；内江师范学院数值仿真四川省高等学校重点实验室，四川 内江
关键词: 多属性群决策；中智Z数；Sugeno-Weber；WASPAS；Multi-Attribute Group Decision-Making； Neutrosophic Z-Number； Sugeno-Weber； WASPAS
摘要: 针对实际决策问题中需要考虑评估信息不确定性和可靠性且属性权重完全未知的情形，本文提出基于中智Z数WASPAS (Weighted aggregated sum product assessment)的多属性决策方法。首先，基于Sugeno-Weber三角模定义中智Z数Sugeno-Weber运算法则并基于该运算提出四种新的中智Z数加权平均和几何算子，同时讨论所提算子的性质。其次，针对属性权重完全未知的决策情形，提出了基于中智Z数得分函数的常数变异系数法权重模型确定属性权重。为解决备选方案的排序问题，基于所提的中智Z数Sugeno-Weber集成算子，提出改进的WASPAS的多属性决策方法。以绿色供应商评价案例进行实证分析验证所提方法的实用性，并通过敏感性分析和对比研究验证所提方法的稳定性及有效性。
Abstract: This study addresses multi-attribute decision-making (MADM) problems where attribute weights are entirely unknown and requires consideration of both the uncertainty and reliability of evaluation information. We propose a novel Neutrosophic Z-number-based WASPAS (Weighted Aggregated Sum Product Assessment) method. Firstly, based on the Sugeno-Weber triangular norm, we define Sugeno-Weber operational rules for Neutrosophic Z-numbers (NZNs) and introduce four new NZN-weighted averaging and geometric aggregation operators using these operations, also discussing their properties. Secondly, for scenarios with completely unknown attribute weights, we develop a constant variation coefficient weighting model utilizing the NZN score function to determine attribute weights. To resolve alternative ranking, an improved WASPAS MADM method is presented, integrating the proposed NZN Sugeno-Weber aggregation operators. The practicality of the method is validated through an empirical case study on green supplier evaluation, while its stability and effectiveness are demonstrated via sensitivity analysis and comparative studies.
文章引用：万国柔, 荣源. 基于中智Z数WASPAS的多属性决策方法[J]. 应用数学进展, 2025, 14(7): 134-148. https://doi.org/10.12677/aam.2025.147352

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