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Differential evolution based on node strength

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F18%3A86100215" target="_blank" >RIV/61989100:27740/18:86100215 - isvavai.cz</a>

  • Alternative codes found

    RIV/61989100:27240/18:86100215

  • Result on the web

    <a href="https://www.inderscienceonline.com/doi/abs/10.1504/IJBIC.2018.090072" target="_blank" >https://www.inderscienceonline.com/doi/abs/10.1504/IJBIC.2018.090072</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1504/IJBIC.2018.090072" target="_blank" >10.1504/IJBIC.2018.090072</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Differential evolution based on node strength

  • Original language description

    In this paper, three novel algorithms for optimisation based on the differential evolution algorithm are devised. The main idea behind those algorithms stems from the observation that differential evolution dynamics can be modelled via complex networks. In our approach, the individuals of the population are modelled by the nodes and the relationships between them by the directed lines of the graph. Subsequent analysis of non-trivial topological features further influence the process of parent selection in the mutation step and replace the traditional approach which is not reflecting the complex relationships between individuals in the population during evolution. This approach represents a general framework which can be applied to various kinds of differential evolution algorithms. We have incorporated this framework with the three well-performing variants of differential evolution algorithms to demonstrate the effectiveness of our contribution with respect to the convergence rate. Two well-known benchmark sets (including 49 functions) are used to evaluate the performance of the proposed algorithms. Experimental results and statistical analysis indicate that the enhanced algorithms perform better or at least comparable to their original versions.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database

  • 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

    <a href="/en/project/GA15-06700S" target="_blank" >GA15-06700S: Unconventional Control of Complex Systems</a><br>

  • Continuities

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

Others

  • Publication year

    2018

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    International Journal of Bio-Inspired Computation

  • ISSN

    1758-0366

  • e-ISSN

  • Volume of the periodical

    11

  • Issue of the periodical within the volume

    1

  • Country of publishing house

    CH - SWITZERLAND

  • Number of pages

    12

  • Pages from-to

    34-45

  • UT code for WoS article

  • EID of the result in the Scopus database

    2-s2.0-85042934914