Nowadays, interval comparison matrices (ICM) take an important role in decision making under uncertainty. So it seems that a brief review on solution methods used in ICM should be useful. In this paper, the common methods are divided into four categories that are Goal Programming Method (GPM), Linear Programming Method (LPM), Non-Linear Programming Method (NLPM) and Statistic Analysis (SA). GPM...

Interval pairwise comparison matrices are widely accepted for practical decision making problems when the maker is unable to provide an exact judgment on alternatives. However, as measuring preference consistencies in important, this paper proposes a new interval matrix consistency measure, average geometric index, that assumes given follows lognormal distribution. This measure accounts boundar...

Interval Pairwise Comparison Matrices have been widely used to account for uncertain statements concerning the preferences of decision makers. Several approaches have been proposed in the literature, such as multiplicative and fuzzy interval matrices. In this paper, we propose a general unified approach to Interval Pairwise Comparison Matrices, based on Abelian linearly ordered groups. In this ...

In this paper analytic hierarchy process (AHP), a well-known approach for handling multi-criteria decision making problems, is discussed. It is based on pairwise comparisons. The methods for deriving the priority vectors from comparison matrices are examined. The existing methods for aggregating the individual comparison matrices into a group comparison matrix are revised. A method for aggregat...

A two-stage logarithmic goal programming (TLGP) method is proposed to generate weights from interval comparison matrices, which can be either consistent or inconsistent. The first stage is devised to minimize the inconsistency of interval comparison matrices and the second stage is developed to generate priorities under the condition of minimal inconsistency. The weights are assumed to be multi...

Crisp comparison matrices produce crisp weight estimates. It is logical for an interval or fuzzy comparison matrix to give an interval or fuzzy weight estimate. In this paper, an eigenvector method (EM) is proposed to generate interval or fuzzy weight estimate from an interval or fuzzy comparison matrix, which differs from Csutora and Buckley’s LambdaMax method in several aspects. First, the pr...

according to the limit of resources in the subject of prioritization, one of the alternative methods is mcdm method. generally, mcdm models have been developed under certainty while we confront with under uncertainty in real world. in hierarchical mcdm methods, one of the main steps is to weigh criteria and computes each alternative weight using defined criteria in the next steps. one of the ea...