Interval weight generation approaches based on consistency test and interval comparison matrices
Applied Mathematics and ComputationPublished 9 February 2005
Ying‐Ming Wang, Jianbo Yang, Dong‐Ling Xu
Citations146
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SJR score0.89
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TL;DR
An eigenvector method-based nonlinear programming (NLP) approach is developed to generate interval weights that can meet pre-determined consistency requirements and a simple and effective preference ranking method is utilized to compare the interval weights of criteria or rank alternatives.
Abstract
A simple yet pragmatic method of consistency test is developed to check whether an interval comparison matrix is consistent or not. Linear programming method is used to derive consistent interval weights from consistent interval comparison matrices and to aggregate local interval weights to generate global interval weights. In cases where an interval comparison matrix is inconsistent, an eigenvector method-based nonlinear programming (NLP) approach is developed to generate interval weights that can meet pre-determined consistency requirements. A simple and effective preference ranking method is utilized to compare the interval weights of criteria or rank alternatives. Three numerical examples including a hierarchical (AHP) decision problem are provided to illustrate the validity and practicality of the proposed methods. © 2004 Elsevier Inc. All rights reserved.
Keywords
Computer ScienceDecision SciencesMathematics
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