Castellanos-Alvarez, Alejandro and Cruz-Reyes, Laura and Fernandez, Eduardo and Rangel-Valdez, Nelson and Gómez-Santillán, Claudia and Fraire, Hector and Brambila-Hernández, José Alfredo (2021) A Method for Integration of Preferences to a Multi-Objective Evolutionary Algorithm Using Ordinal Multi-Criteria Classification. Mathematical and Computational Applications, 26 (2). p. 27. ISSN 2297-8747
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Abstract
Most real-world problems require the optimization of multiple objective functions simultaneously, which can conflict with each other. The environment of these problems usually involves imprecise information derived from inaccurate measurements or the variability in decision-makers’ (DMs’) judgments and beliefs, which can lead to unsatisfactory solutions. The imperfect knowledge can be present either in objective functions, restrictions, or decision-maker’s preferences. These optimization problems have been solved using various techniques such as multi-objective evolutionary algorithms (MOEAs). This paper proposes a new MOEA called NSGA-III-P (non-nominated sorting genetic algorithm III with preferences). The main characteristic of NSGA-III-P is an ordinal multi-criteria classification method for preference integration to guide the algorithm to the region of interest given by the decision-maker’s preferences. Besides, the use of interval analysis allows the expression of preferences with imprecision. The experiments contrasted several versions of the proposed method with the original NSGA-III to analyze different selective pressure induced by the DM’s preferences. In these experiments, the algorithms solved three-objectives instances of the DTLZ problem. The obtained results showed a better approximation to the region of interest for a DM when its preferences are considered.
Item Type: | Article |
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Uncontrolled Keywords: | incorporation of preferences; multi-criteria classification; decision-making process; multi-objective evolutionary optimization; outranking relationships |
Subjects: | SCI Archives > Mathematical Science |
Depositing User: | Managing Editor |
Date Deposited: | 12 Nov 2022 07:17 |
Last Modified: | 02 Jul 2024 04:10 |
URI: | http://science.classicopenlibrary.com/id/eprint/133 |