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Non-uniqueness of Interval Weight Vector to Consistent Interval Pairwise Comparison Matrix and Logarithmic Estimation Methods

机译:区间权向量对一致区间成对比较矩阵的非唯一性和对数估计方法

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In this paper we investigate the interval priority weight estimation from a given interval pairwise comparison matrix. The lower and upper models as well as goal programming model were proposed. It has been expected that the sum of widths of interval weights estimated by lower model is not greater than that estimated by upper model. We show that this expectation is not always hold. Especially when the given interval comparison matrix is totally consistent, it is possible that the solution is not unique and the reverse inequality relation holds. We investigate uniqueness conditions of interval comparison matrices and the influence of non-uniqueness in the comparison of alternatives. Based on the results of investigation above, we propose interval weight estimation methods from interval pairwise comparison matrix.
机译:在本文中,我们从给定的间隔成对比较矩阵中研究了间隔优先权重估计。提出了下层和上层模型以及目标规划模型。可以预料的是,下层模型估计的区间权重的宽度之和不大于上层模型估计的区间权重的宽度之和。我们证明这种期望并不总是成立。特别是当给定的间隔比较矩阵完全一致时,解决方案可能不是唯一的,并且反向不等式关系成立。我们研究区间比较矩阵的唯一性条件以及非唯一性在替代方案比较中的影响。基于以上研究结果,提出了基于区间对比较矩阵的区间权重估计方法。

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