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Exploring the Frequency of Boundary Control Methods Activation in Metaheuristic Algorithms

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F23%3A63563678" target="_blank" >RIV/70883521:28140/23:63563678 - isvavai.cz</a>

  • Result on the web

    <a href="https://dl.acm.org/doi/10.1145/3583133.3596418" target="_blank" >https://dl.acm.org/doi/10.1145/3583133.3596418</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1145/3583133.3596418" target="_blank" >10.1145/3583133.3596418</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Exploring the Frequency of Boundary Control Methods Activation in Metaheuristic Algorithms

  • Original language description

    Recently, Boundary Control Methods (BCMs) have become increasingly relevant in the field of metaheuristic algorithms. In this study, we investigate the relationship between the activation frequency of different BCMs and the problem&apos;s dimensionality. Additionally, we analyze each problem dimension independently. Our research primarily concentrates on the top three algorithms from the IEEE CEC 2020 competition: AGSK, IMODE, and j2020, utilizing the competition benchmark set to conduct experiments. Our findings provide valuable insights into the metaheuristic domain, underlining the significance of comprehending BCM activation patterns to improve algorithm design and benchmarking practices.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    GECCO 2023 Companion - Proceedings of the 2023 Genetic and Evolutionary Computation Conference Companion

  • ISBN

    979-840070120-7

  • ISSN

  • e-ISSN

  • Number of pages

    7

  • Pages from-to

    2330-2336

  • Publisher name

    Association for Computing Machinery, Inc

  • Place of publication

    New York

  • Event location

    Lisbon

  • Event date

    Jul 15, 2023

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article