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Publikační činnost

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Typ záznamu:	článek v odborném periodiku (J)
Domácí pracoviště:	Katedra informatiky a počítačů (31400)
Název:	Synchronous and Asynchronous Migration in Adaptive Differential Evolution Algorithms
Citace	Bujok, P. Synchronous and Asynchronous Migration in Adaptive Differential Evolution Algorithms. NEURAL NETWORK WORLD. 2013, č. 23, s. 17-30. ISSN 1210-0552.

Podnázev
Rok vydání:	2013
Obor:	Informatika
Kód ISSN:	1210-0552
Oficiální název periodika:	NEURAL NETWORK WORLD
Stát vydavatele periodika:	Česká republika
Svazek periodika:	23
Číslo periodika v rámci svazku:	1
Číslo článku:
Ročník:
Počet stran článku:	14
Strana od:	17
Strana do:	30
Kód UT WoS:
EID:
Poddruh recenzovaného článku:	Článek v impaktovaném časopise (Jimp)

Klíčová slova anglicky:	Differential evolution, parallel migration model, synchronous migration, asynchronous migration, benchmark problems, experimental comparison
Popis v původním jazyce:	The influence of synchronous and asynchronous migration on the performance of adaptive differential evolution algorithms is investigated. Six adaptive differential evolution variants are employed by the parallel migration model with a~star topology. Synchronous and asynchronous migration models with various parameters settings were experimentally compared with non-parallel adaptive algorithms in six shifted benchmark problems of dimension D=30. Three different ways of exchanging individuals are applied in a synchronous island model with a fixed number of islands. Three different numbers of sub-populations are set up in an asynchronous island model. The parallel synchronous and asynchronous migration models increase performance in most problems.
Popis v anglickém jazyce:	The influence of synchronous and asynchronous migration on the performance of adaptive differential evolution algorithms is investigated. Six adaptive differential evolution variants are employed by the parallel migration model with a~star topology. Synchronous and asynchronous migration models with various parameters settings were experimentally compared with non-parallel adaptive algorithms in six shifted benchmark problems of dimension D=30. Three different ways of exchanging individuals are applied in a synchronous island model with a fixed number of islands. Three different numbers of sub-populations are set up in an asynchronous island model. The parallel synchronous and asynchronous migration models increase performance in most problems.

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Ohlas

R01:	RIV/61988987:17310/13:A13015U5

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