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Partial Population Restart of Firefly Algorithm Using Complex Network Analysis

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F17%3A63517191" target="_blank" >RIV/70883521:28140/17:63517191 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Partial Population Restart of Firefly Algorithm Using Complex Network Analysis

  • Original language description

    In this paper, we are presenting a method for controlling population diversity of popular metaheuristic algorithm, which is the Firefly Algorithm (FA). Presented method is using the advantages of complex networks and their several characteristics, that can be helpful for the detailed analysis of metaheuristic algorithm inner dynamic. However, this application can be quite tricky, since there are too many possibilities, as to how to use the advantages of complex networks analysis approach. Through this work, we are trying to present a simple workflow for building and analysis of network and the most suitable choices in each step to achieve better results of FA, especially, when focusing on population diversity.

  • 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

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2017

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    2017 IEEE Symposium Series on Computational Intelligence (SSCI) Proceedings

  • ISBN

    978-1-5386-2725-9

  • ISSN

  • e-ISSN

    neuvedeno

  • Number of pages

    6

  • Pages from-to

    2505-2511

  • Publisher name

    IEEE

  • Place of publication

    New Jersey, Piscataway

  • Event location

    Honolulu, Hawai

  • Event date

    Nov 27, 2017

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article