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  4. A metaheuristic approach to improve consistency of the pairwise matrix in AHP

A metaheuristic approach to improve consistency of the pairwise matrix in AHP

MMC.
2023;
Volume 10, Number 4
: pp. 1164–1173
https://doi.org/10.23939/mmc2023.04.1164
Received: August 20, 2023
Revised: November 02, 2023
Accepted: November 03, 2023

Mathematical Modeling and Computing, Vol. 10, No. 4, pp. 1164–1173 (2023)

Authors:
  1. Z. Tajani
  2. C. Tajani
  3. I. Khattabi
  4. M. Sabbane
1
Faculty of Sciences, Moulay Ismail University
2
Polydisciplinary Faculty of Larache, Abdelmalek Essaadi University
3
Polydisciplinary Faculty of Larache, Abdelmalek Essaadi University
4
Faculty of Sciences, Moulay Ismail University

In this paper, we are interested in modifying inconsistent pairwise comparison matrix which is a critical step in the AHP methodology, where decision makers have to improve the consistency by revising the process.  To this end, we propose an improved genetic algorithm (GA) to allow decision makers to find an appropriate matrix and adjust the consistency of their judgment without loss of original comparison matrix.  Numerical results with different dimensions of matrices taken randomly show the effectiveness of these strategy to improve and identify the consistency of pairwise matrix which mean that GAs are a very good tool to generate the consistent pairwise comparison matrices with different number of criteria.

genetic algorithm
pairwise matrix
analytic hierarchy process
decision theory
consistency
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