Abstract
AbstractIn this paper, we investigate the significance of interval weight estimation in the setting of Analytic Hierarchy Process (AHP). We consider several estimation methods for a normalized interval weight vector from a crisp pairwise comparison matrix. They have a desirable property. To avoid the non-uniqueness of the solution, we add an additional constraint, i.e., the sum of centers of interval weights is one. A few ranking methods under interval weights are considered. Numerical experiments are executed to compare the estimation accuracy of ranking alternatives under the assumption that the decision maker has a true interval weight vector. The advantage of interval weight estimation over crisp weight estimation is demonstrated.KeywordsInterval weight estimationAHPPairwise comparison matrixLinear programming
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