MATEC Web Conf.
Volume 76, 201620th International Conference on Circuits, Systems, Communications and Computers (CSCC 2016)
|Number of page(s)||4|
|Published online||21 October 2016|
Priority Derivation from Pairwise Comparison Matrices by Multi-Objective Evolutionary Computing
Manchester Business School, University of Manchester, Manchester, United Kingdom
a Email address: email@example.com
The paper investigates the application of evolutionary algorithms (EA) for solving prioritisation problems, in the framework of the Analytical Hierarchy Process. A new two-objective prioritization (TOP) method was proposed recently by the author, where the prioritisation problem is formulated as an optimization task for minimization of the Euclidean norm and the number of rank violations. The TOP method derives Pareto optimal solutions, which requires the application of efficient computational algorithms. We propose two evolutionary computing approaches, based on single-objective and multi-objective evolutionary algorithms. Our preliminary results from a Monte-Carlo simulation show that the multi-objective EA outperforms the single-objective solution approach with respect to accuracy and computational efficiency.
© The Authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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