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Axiomatic property based consistency analysis and decision making with interval multiplicative reciprocal preference relations

机译:间隔乘法互惠偏好关系的基于公理性基于的一致性分析与决策

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This paper focuses on obtaining an interval extension of Saaty's consistency and eliciting normalized interval weights in analytic form from interval multiplicative reciprocal preference relations (IMRPRs) as well as checking acceptability of IMRPRs. Four axiomatic properties are presented to characterize multiplicative consistency of IMRPRs. The paper shows that six existing consistency definitions fail to satisfy all the four axiomatic properties. A constrained interval multiplication based transitivity equation is devised and an interval matrix is constructed to capture original preferences and row uncertainty proportionalities of an IMRPR. Based on the constructed interval matrix, an ordinary interval multiplication based transitivity equation is developed to define consistency of IMRPRs. A logarithmic least square model is established to find normalized interval weights from IMRPRs and its analytic solution is obtained by the Lagrangian multiplier method. The paper introduces an index to measure uniformity of row uncertainties in an IMRPR and proposes a geometric consistency index to measure inconsistency of IMRPRs. A novel method is put forward to determine acceptability of IMRPRs by checking acceptable consistency and acceptable uncertainty. The proposed models are illustrated by eight numerical examples and a hierarchical multi-criteria decision making problem dealing with recommending undergraduate students to graduate admission. (C) 2019 Elsevier Inc. All rights reserved.
机译:本文侧重于从区间乘法互惠偏好关系(IMRPRS)的分析形式中获得SAATY的一致性和诱导归一化间隔权重的间隔扩展,以及检查IMRPRS的可接受性。提出了四个公理性质以表征IMRPRS的乘法一致性。本文表明,六个现有的一致性定义未能满足所有四个公理性质。设计了受约束的间隔乘法的转运方程,并且构造间隔矩阵以捕获IMRPR的原始偏好和行不确定性比例。基于构造间隔矩阵,开发了一种普通的间隔乘法的传递性方程来定义IMRPRS的一致性。建立一个对数最小二乘模型,以找到来自IMRPRS的归一化间隔权重,并通过拉格朗日乘法器方法获得其分析解决方案。本文介绍了一种索引,以测量IMRPR中行不确定性的均匀性,并提出了几何一致性指标来测量IMRPRS的不一致。提出了一种新的方法来通过检查可接受的一致性和可接受的不确定性来确定IMRPRS的可接受性。所提出的模型由八个数值示例和分层多标准决策进行说明,处理推荐本科生毕业的问题。 (c)2019 Elsevier Inc.保留所有权利。

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