Decomposition descent method for limit optimization problems

dc.contributor.author	Konnov I.
dc.date.accessioned	2018-04-05T07:09:20Z
dc.date.available	2018-04-05T07:09:20Z
dc.date.issued	2017
dc.identifier.issn	0302-9743
dc.identifier.uri	http://dspace.kpfu.ru/xmlui/handle/net/129657
dc.description.abstract	© Springer International Publishing AG 2017. We consider a general limit optimization problem whose goal function need not be smooth in general and only approximation sequences are known instead of exact values of this function. We suggest to apply a two-level approach where approximate solutions of a sequence of mixed variational inequality problems are inserted in the iterative scheme of a selective decomposition descent method. Its convergence is attained under coercivity type conditions.
dc.relation.ispartofseries	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.subject	Coercivity conditions
dc.subject	Decomposition descent method
dc.subject	Limit problems
dc.subject	Mixed variational inequality
dc.subject	Non-smooth functions
dc.subject	Optimization problems
dc.title	Decomposition descent method for limit optimization problems
dc.type	Conference Paper
dc.relation.ispartofseries-volume	10556 LNCS
dc.collection	Публикации сотрудников КФУ
dc.relation.startpage	166
dc.source.id	SCOPUS03029743-2017-10556-SID85034268458

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Публикации сотрудников КФУ Scopus [24551]
Коллекция содержит публикации сотрудников Казанского федерального (до 2010 года Казанского государственного) университета, проиндексированные в БД Scopus, начиная с 1970г.