Reconstructing pairwise comparisons matrices based on differential evolution: a Monte Carlo study
Date
2021-05-28
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Abstract
Pairwise comparisons have been used in the decision-making process since
antiquities. However, it is a substantial challenge to generate a PC matrix
from noisy or incomplete real-life input data. This study aims to investigate
the reconstruction of pairwise comparisons matrices from not-so-inconsistent
pairwise comparisons matrices by an optimization method based on diāµerential evolution. A distance-based objective function is defined as a function
of the inconsistency indicator and the distance metric. Monte Carlo experiments are designed to illustrate the research outcomes. The experimental
results show that this method convergence quickly. It also provides comparisons of several traditional metrics.
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Keywords
Pairwise comparisons, pairwise comparisons matrix, inconsistency, differential evolution, optimization,, Monte Carlo,, metric