Differential Evolution with Exponential Crossover Revisited
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17310%2F16%3AA1701H3A" target="_blank" >RIV/61988987:17310/16:A1701H3A - isvavai.cz</a>
Výsledek na webu
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DOI - Digital Object Identifier
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Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Differential Evolution with Exponential Crossover Revisited
Popis výsledku v původním jazyce
The influence of exponential crossover on the performance of differential evolution (DE) is studied experimentally. Nine DE variants known from literature are selected for experimental comparison. Four selected DE variants come from the state-of-the-art set, four algorithms are chosen from recently published well-performing DE variants and the last algorithm is standard classical DE. The experimental comparison was carried out in pairwise manner, the performance of two variants of each selected algorithm (one using binomial crossover and the latter variant using exponential crossover) was compared on each problem of CEC 2011 real-world optimization benchmark. The DE variants with exponential crossover outperformed signicantly the binomial-crossover counterparts in the algorithms, in four algorithms the performance was approximately equal, and only in jDE case the variant with binomial crossover outperformed signicantly the counterpart in nine test problems, while it was signicantly worse in four problems. The results show that the application of DE strategies with the exponential crossover is beneficial in the design of new adaptive DE variants.
Název v anglickém jazyce
Differential Evolution with Exponential Crossover Revisited
Popis výsledku anglicky
The influence of exponential crossover on the performance of differential evolution (DE) is studied experimentally. Nine DE variants known from literature are selected for experimental comparison. Four selected DE variants come from the state-of-the-art set, four algorithms are chosen from recently published well-performing DE variants and the last algorithm is standard classical DE. The experimental comparison was carried out in pairwise manner, the performance of two variants of each selected algorithm (one using binomial crossover and the latter variant using exponential crossover) was compared on each problem of CEC 2011 real-world optimization benchmark. The DE variants with exponential crossover outperformed signicantly the binomial-crossover counterparts in the algorithms, in four algorithms the performance was approximately equal, and only in jDE case the variant with binomial crossover outperformed signicantly the counterpart in nine test problems, while it was signicantly worse in four problems. The results show that the application of DE strategies with the exponential crossover is beneficial in the design of new adaptive DE variants.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
IN - Informatika
OECD FORD obor
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Návaznosti výsledku
Projekt
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Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2016
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
MENDEL 2016 22nd International Conference on Soft Computing
ISBN
978-80-214-5365-4
ISSN
1803-3814
e-ISSN
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Počet stran výsledku
8
Strana od-do
17-24
Název nakladatele
Brno University of Technology
Místo vydání
Brno
Místo konání akce
Brno
Datum konání akce
7. 6. 2016
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
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