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Desirable Objective Ranges in Preference-Based Evolutionary Multiobjective Optimization

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Applications of Evolutionary Computation (EvoApplications 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12694))

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Abstract

In this paper, we propose a preference-based Evolutionary Multiobjective Optimization algorithm, at which the preferences are given in the form of desirable ranges for the objective functions, i.e. by means of aspiration and reservation levels. The aspiration levels are values to be achieved by the objectives, while the reservation levels are objective values not to be worsen. In the algorithm proposed, the first generations are performed using a set of weight vectors to initially converge to the region of the Pareto optimal front associated with the point formed with the reservation levels. At a certain moment, these weights are updated using the nondominated solutions generated so far, to re-direct the search towards the region which contains the Pareto optimal solutions with objective values among the desirable ranges. To this aim, the remaining number of generations are run using the updated weight vectors and the point formed with the aspiration levels. The computational experiment show the potential of our proposal in 2, 3 and 5-objective problems, in comparison to other state-of-the-art algorithms.

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Notes

  1. 1.

    The code is available upon request to any of the authors.

  2. 2.

    https://stat.ethz.ch/R-manual/R-devel/library/stats/html/wilcox.test.html.

  3. 3.

    https://cran.r-project.org/web/packages/effsize/.

  4. 4.

    This means that the difference between the distributions is not significant.

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Acknowledgements

This work has been supported by the Spanish Ministry of Economy and Competitiveness (project ECO2017-88883-R), and by the Andalusian Regional Ministry of Economy, Knowledge, Business and University (PAI group SEJ-532 and UMA18-FEDERJA-024). Sandra González-Gallardo is recipient of a technical research contract within “Sistema Nacional de Garantia Juvenil y del Programa Operativo de Empleo Juvenil 2014–2020 - Fondos FEDER”. Rubén Saborido is recipient of a Juan de la Cierva grant (reference FJC2018-038537-I), funded by the Spanish State Research Agency.

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Authors and Affiliations

  1. Department of Applied Economics (Mathematics), University of Málaga, Málaga, Spain

    Sandra González-Gallardo, Ana B. Ruiz & Mariano Luque

  2. ITIS Software, University of Málaga, Málaga, Spain

    Rubén Saborido

Authors
  1. Sandra González-Gallardo
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  2. Rubén Saborido
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  3. Ana B. Ruiz
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  4. Mariano Luque
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Correspondence to Sandra González-Gallardo .

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Editors and Affiliations

  1. ETSIIT-CITIC, University of Granada, Granada, Spain

    Pedro A. Castillo

  2. Université Le Havre Normandie, Le Havre, France

    Juan Luis Jiménez Laredo

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González-Gallardo, S., Saborido, R., Ruiz, A.B., Luque, M. (2021). Desirable Objective Ranges in Preference-Based Evolutionary Multiobjective Optimization. In: Castillo, P.A., Jiménez Laredo, J.L. (eds) Applications of Evolutionary Computation. EvoApplications 2021. Lecture Notes in Computer Science(), vol 12694. Springer, Cham. https://doi.org/10.1007/978-3-030-72699-7_15

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  • DOI: https://doi.org/10.1007/978-3-030-72699-7_15

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