Comparison of Nature-Inspired Population-Based Algorithms on Continuous Optimisation Problems
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17310%2F19%3AA2001T2N" target="_blank" >RIV/61988987:17310/19:A2001T2N - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S2210650218301536" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2210650218301536</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.swevo.2019.01.006" target="_blank" >10.1016/j.swevo.2019.01.006</a>
Alternative languages
Result language
angličtina
Original language name
Comparison of Nature-Inspired Population-Based Algorithms on Continuous Optimisation Problems
Original language description
Nine nature-inspired algorithms are compared with four advanced adaptive differential evolution (DE) variants, the classic DE and the blind randomsearch on two benchmark sets. One of the benchmark sets is the CEC 2011 collection of 22 real-world optimization problems, the latter is the suite of30 artificial optimization problems defined for the competition of the algorithms within CEC 2014. The results of the experiments demonstrate the superiority of the adaptive DE variants both on the real-world problems and the artificial CEC 2014 test suite at all the levels of dimension (10, 30, and50). Some of the nature-inspired algorithms perform even worse than the blind random search. The efficiency of the classic DE is comparable with the better performing nature-inspired methods. The results entitle to form a recommendation for practitioners: Do not propose a new original algorithm but select from the optimization algorithms supported by thorough researchand good ranking at international competitions of optimization algorithms.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10102 - Applied mathematics
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Swarm and Evolutionary Computation
ISSN
2210-6502
e-ISSN
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Volume of the periodical
50
Issue of the periodical within the volume
NOV2019
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
10
Pages from-to
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UT code for WoS article
000497252300028
EID of the result in the Scopus database
2-s2.0-85061284824