Publ3 search

Error:

Javascript is disabled in this browser. This page requires Javascript. Modify your browser's settings to allow Javascript to execute. See your browser's documentation for specific instructions.

Publikační činnost

Probíhá načítání, čekejte prosím...

Typ záznamu * :	stať ve sborníku (D)
Domácí pracoviště * :	Katedra matematiky (31100)
Název * :	Competing Heuristics-Experimental Study
Citace :	Tvrdík, J., Křivý, I. a Mišík, L. Competing Heuristics-Experimental Study. In: MENDEL 2002, 8th International Conference on Soft Computing (Matoušek R. and Ošmera P. eds): MENDEL 2002, 8th International Conference on Soft Computing 2002-06-05 Brno. Brno: VUT Brno, 2002. VUT Brno, 2002. s. 74-79. ISBN 80-214-2135-5.

Podnázev :
Rok * :	2002
Obor * :	Aplikovaná statistika, operační výzkum
Počet stran * :	6
Strana od * :	74
Strana do * :	79
Forma vydání * :
Kód ISBN * :	80-214-2135-5
Kód ISSN :
Název sborníku * :	MENDEL 2002, 8th International Conference on Soft Computing
Sborník :	Mezinárodní
Název nakladatele * :	VUT Brno
Místo vydání * :	Brno
Stát vydání :	Sborník vydaný v ČR
Název konference :	MENDEL 2002, 8th International Conference on Soft Computing (Matoušek R. and Ošmera P. eds)
Místo konání konference * :	Brno
Datum zahájení konference * :
Typ akce podle státní příslušnosti účastníků akce * :	Celosvětová akce
Kód UT WoS :
EID :

Klíčová slova anglicky * :	global optimization; evolutionary algorithms; competing heuristics; self-adaptation of algorithm
Popis v původním jazyce * :	The aim of this paper is to study the properties of evolutionary algorithms with competing heuristics in dependence on several factors like the number of heuristics in competition, the values of their tuning parameters, the rules of competition and so on. Thirty six heuristics were implemented and their role in the evolutionary process was investigated. The optimization experiments were done with several well-known test functions (DeJong 1 and 2, Ackley, Griewangk). The main variables measured in experiments were the number of the objective function evaluations needed for reaching the stopping condition and the reliability of finding a point very near to the global minimum. The evolutionary algorithms with competing heuristics were more efficient than other evolutionary algorithms in some tasks.
Popis v anglickém jazyce * :	The aim of this paper is to study the properties of evolutionary algorithms with competing heuristics in dependence on several factors like the number of heuristics in competition, the values of their tuning parameters, the rules of competition and so on. Thirty six heuristics were implemented and their role in the evolutionary process was investigated. The optimization experiments were done with several well-known test functions (DeJong 1 and 2, Ackley, Griewangk). The main variables measured in experiments were the number of the objective function evaluations needed for reaching the stopping condition and the reliability of finding a point very near to the global minimum. The evolutionary algorithms with competing heuristics were more efficient than other evolutionary algorithms in some tasks.

Typ zdroje financování výsledku * :

Projekty CEP/Záměry CEZ

Seznam projektů :

ID Projektu	Název projektu

Seznam ohlasů :

Ohlas

R01:	RIV/61988987:17310/02:00000015

Complementary Content

${loading}