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Extension of the LINMAP for multiattribute decision making under Atanassov’s intuitionistic fuzzy environment

机译:在Atanassov的直觉模糊环境下扩展LINMAP以进行多属性决策

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The aim of this article is further extending the linear programming techniques for multidimensional analysis of preference (LINMAP) to develop a new methodology for solving multiattribute decision making (MADM) problems under Atanassov’s intuitionistic fuzzy (IF) environments. The LINMAP only can deal with MADM problems in crisp environments. However, fuzziness is inherent in decision data and decision making processes. In this methodology, Atanassov’s IF sets are used to describe fuzziness in decision information and decision making processes by means of an Atanassov’s IF decision matrix. A Euclidean distance is proposed to measure the difference between Atanassov’s IF sets. Consistency and inconsistency indices are defined on the basis of preferences between alternatives given by the decision maker. Each alternative is assessed on the basis of its distance to an Atanassov’s IF positive ideal solution (IFPIS) which is unknown a prior. The Atanassov’s IFPIS and the weights of attributes are then estimated using a new linear programming model based upon the consistency and inconsistency indices defined. Finally, the distance of each alternative to the Atanassov’s IFPIS can be calculated to determine the ranking order of all alternatives. A numerical example is examined to demonstrate the implementation process of this methodology. Also it has been proved that the methodology proposed in this article can deal with MADM problems under not only Atanassov’s IF environments but also both fuzzy and crisp environments.
机译:本文的目的是进一步扩展用于偏好的多维分析(LINMAP)的线性编程技术,以开发一种新的方法来解决Atanassov的直觉模糊(IF)环境下的多属性决策(MADM)问题。 LINMAP仅能在较脆的环境中处理MADM问题。但是,模糊性是决策数据和决策过程中固有的。在这种方法中,Atanassov的IF集用于通过Atanassov的IF决策矩阵来描述决策信息和决策过程中的模糊性。提出了一个欧几里得距离来测量Atanassov的IF集之间的差异。一致性和不一致指数是根据决策者提供的备选方案之间的偏好来定义的。每个备选方案都是根据其与Atanassov的IF正理想解决方案(IFPIS)的距离进行评估的,该解决方案以前是未知的。然后,根据定义的一致性和不一致性指标,使用新的线性规划模型估算Atanassov的IFPIS和属性的权重。最后,可以计算出每个替代方案与Atanassov的IFPIS的距离,以确定所有替代方案的排名顺序。数值实例进行了检验,以证明该方法的实施过程。也已经证明,本文提出的方法不仅可以处理Atanassov的IF环境下的MADM问题,而且还可以处理模糊和清晰环境下的MADM问题。

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