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首页> 外文期刊>Journal of information and computational science >Dynamic Multi-attribute Decision Making Based on Advantage Retention Degree
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Dynamic Multi-attribute Decision Making Based on Advantage Retention Degree

机译:基于优势保留度的动态多属性决策

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This paper investigates the Dynamic Multi-attribute Decision Making (DMADM) problems, in which all the attribute values provided by decision maker at different periods take the form of triangular fuzzy linguistic variables, and develops an interactive method to solve the DMADM problems. The notions of triangular fuzzy number and calculation formula for possibility-degree of triangular fuzzy number based on area proportion are defined. According to the logic continuity of decision results at adjoining periods, the concept of retain ability is described. The developed method firstly aggregates the attribute value to construct a possibility-degree matrix by using the Triangular Fuzzy Language Weighted Averaging (TFLWA) operator, then calculates the dynamic ordering vector based on Advantage Retention Degree (ARD) at different, periods. After that, the method ranks the alternatives in accordance with the values of final dynamic ordering vector based on ARD, so that the optimal alternative can be selected. Finally, an illustrative example is given to verify the developed approach and demonstrate its practicality and effectiveness.
机译:本文研究了动态多属性决策(DMADM)问题,其中决策者在不同时期提供的所有属性值都采用三角模糊语言变量的形式,并开发了一种交互式方法来解决DMADM问题。定义了三角模糊数的概念和基于面积比例的三角模糊数的可能性度的计算公式。根据相邻阶段决策结果的逻辑连续性,描述了保持能力的概念。所开发的方法首先使用三角模糊语言加权平均(TFLWA)运算符聚合属性值以构建可能性度矩阵,然后基于不同时期的优势保留度(ARD)计算动态排序向量。此后,该方法根据基于ARD的最终动态排序向量的值对备选方案进行排序,从而可以选择最佳备选方案。最后,给出了一个示例来验证所开发的方法并证明其实用性和有效性。

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