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
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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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
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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
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EID of the result in the Scopus database
2-s2.0-85042934914