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An Analysis of a KNN Perturbation Operator: An Application to the Binarization of Continuous Metaheuristics

Author

Listed:
  • José García

    (Escuela de Ingeniería en Construcción, Pontificia Universidad Católica de Valparaíso, Valparaíso 2362807, Chile
    These authors contributed equally to this work.)

  • Gino Astorga

    (Escuela de Negocios Internacionales, Universidad de Valparaíso, Valparaíso 2361864, Chile
    These authors contributed equally to this work.)

  • Víctor Yepes

    (Institute of Concrete Science and Technology (ICITECH), Universitat Politècnica de València, 46022 València, Spain
    These authors contributed equally to this work.)

Abstract

The optimization methods and, in particular, metaheuristics must be constantly improved to reduce execution times, improve the results, and thus be able to address broader instances. In particular, addressing combinatorial optimization problems is critical in the areas of operational research and engineering. In this work, a perturbation operator is proposed which uses the k-nearest neighbors technique, and this is studied with the aim of improving the diversification and intensification properties of metaheuristic algorithms in their binary version. Random operators are designed to study the contribution of the perturbation operator. To verify the proposal, large instances of the well-known set covering problem are studied. Box plots, convergence charts, and the Wilcoxon statistical test are used to determine the operator contribution. Furthermore, a comparison is made using metaheuristic techniques that use general binarization mechanisms such as transfer functions or db-scan as binarization methods. The results obtained indicate that the KNN perturbation operator improves significantly the results.

Suggested Citation

  • José García & Gino Astorga & Víctor Yepes, 2021. "An Analysis of a KNN Perturbation Operator: An Application to the Binarization of Continuous Metaheuristics," Mathematics, MDPI, vol. 9(3), pages 1-20, January.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:3:p:225-:d:486085
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    References listed on IDEAS

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    Cited by:

    1. José García & Paola Moraga & Broderick Crawford & Ricardo Soto & Hernan Pinto, 2022. "Binarization Technique Comparisons of Swarm Intelligence Algorithm: An Application to the Multi-Demand Multidimensional Knapsack Problem," Mathematics, MDPI, vol. 10(17), pages 1-20, September.
    2. José García & José Lemus-Romani & Francisco Altimiras & Broderick Crawford & Ricardo Soto & Marcelo Becerra-Rozas & Paola Moraga & Alex Paz Becerra & Alvaro Peña Fritz & Jose-Miguel Rubio & Gino Astor, 2021. "A Binary Machine Learning Cuckoo Search Algorithm Improved by a Local Search Operator for the Set-Union Knapsack Problem," Mathematics, MDPI, vol. 9(20), pages 1-19, October.
    3. Marcelo Becerra-Rozas & José Lemus-Romani & Felipe Cisternas-Caneo & Broderick Crawford & Ricardo Soto & Gino Astorga & Carlos Castro & José García, 2022. "Continuous Metaheuristics for Binary Optimization Problems: An Updated Systematic Literature Review," Mathematics, MDPI, vol. 11(1), pages 1-32, December.

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