Inferring efficient weights from pairwise comparison matrices

DOI10.1007/s00186-006-0077-1zbMath1132.90007OpenAlexW2037485150MaRDI QIDQ857943

Emilio Carrizosa, Eduardo Conde, Rafael Blanquero

Publication date: 5 January 2007

Published in: Mathematical Methods of Operations Research (Search for Journal in Brave)

Full work available at URL: https://idus.us.es/xmlui/handle/11441/47872

zbMATH Keywords

optimizationfractional programmingdecision analysismulti-objective

Mathematics Subject Classification ID

Quadratic programming (90C20) Fractional programming (90C32) Management decision making, including multiple objectives (90B50)

Related Items (18)

On combinatorial optimization motivated by biology ⋮ On the extraction of weights from pairwise comparison matrices ⋮ Inefficient weights from pairwise comparison matrices with arbitrarily small inconsistency ⋮ Efficient weight vectors from pairwise comparison matrices ⋮ Efficient vectors for double perturbed consistent matrices ⋮ Eigenproblem driven triangular fuzzy analytic hierarchy process ⋮ Efficiency of any weighted geometric mean of the columns of a reciprocal matrix ⋮ Efficient Vectors for Block Perturbed Consistent Matrices ⋮ On approximate monetary unit sampling ⋮ EFFECTIVENESS ANALYSIS OF DERIVING PRIORITY VECTORS FROM RECIPROCAL PAIRWISE COMPARISON MATRICES ⋮ A characterization of the logarithmic least squares method ⋮ Deriving priorities from inconsistent PCM using network algorithms ⋮ An exact global optimization method for deriving weights from pairwise comparison matrices ⋮ Notes on the existence of a solution in the pairwise comparisons method using the heuristic rating estimation approach ⋮ On the monotonicity of the eigenvector method ⋮ Efficient vectors for simple perturbed consistent matrices ⋮ A linear optimization problem to derive relative weights using an interval judgement matrix ⋮ Efficiency of the principal eigenvector of some triple perturbed consistent matrices

Uses Software

• Maple
• INTPAK

Cites Work

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• Eigenvector and logarithmic least squares
• Deriving weights from pairwise comparison ratio matrices: An axiomatic approach
• A scaling method for priorities in hierarchical structures
• A model for the relative importance of the criteria in the multiplicative AHP and SMART
• How to compute least infeasible flows
• A common framework for deriving preference values from pairwise comparison matrices
• Pareto-optimality in linear regression
• A note on the use of goal programming for the multiplicative AHP
• A Goal Programming Method for Generating Priority Vectors

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