A genetic algorithm with expansion and exploration operators for the maximum satisfiability problem

Please use this identifier to cite or link to this item: http://elar.urfu.ru/handle/10995/26839

Title:	A genetic algorithm with expansion and exploration operators for the maximum satisfiability problem
Authors:	Gorbenko, A. Popov, V.
Issue Date:	2013
Citation:	Gorbenko A. A genetic algorithm with expansion and exploration operators for the maximum satisfiability problem / A. Gorbenko, V. Popov // Applied Mathematical Sciences. — 2013. — Vol. 7. — № 21-24. — P. 1183-1190.
Abstract:	There are many problems that standard genetic algorithms fail to solve. Refinements of standard genetic algorithms that can be used to solve hard problems has caused considerable interest. In this paper, we consider genetic algorithms withexpansion and exploration operators for the maximum satisfiability problem.
Keywords:	EXPANSION OPERATOR EXPLORATION OPERATOR GENETIC ALGORITHMS MAXIMUM SATISFIABILITY
URI:	http://elar.urfu.ru/handle/10995/26839
SCOPUS ID:	84873421686
PURE ID:	906022
ISSN:	1312-885X
Appears in Collections:	Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC

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