DSpace Repository

Statistical cluster points and turnpike theorem in nonconvex problems

Show simple item record

dc.creator Mamedov, MA
dc.creator Pehlivan, Serpil
dc.date 2001-04-14T21:00:00Z
dc.date.accessioned 2020-10-06T09:48:48Z
dc.date.available 2020-10-06T09:48:48Z
dc.identifier 42f36a2c-d257-4ae7-aa7c-94b1cdcbe4d6
dc.identifier 10.1006/jmaa.2000.7061
dc.identifier https://avesis.sdu.edu.tr/publication/details/42f36a2c-d257-4ae7-aa7c-94b1cdcbe4d6/oai
dc.identifier.uri http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/58569
dc.description In this paper we develop the method suggested by S. Pchlivan and M. A. Mamedov ("Statistical Cluster Points and Turnpike," submitted), where it was proved that under some conditions optimal paths have the same unique stationary limit point-stationary cluster point. This notion was introduced by J. A. Fridy (1993, Proc. Amer. Math. Sec. 118, 1187-1192) and it turns out to he a very useful and interesting tool in turnpike theory. The purpose of this paper is to avoid the convexity conditions. Here the turnpike theorem is proved under conditions that are quite different from those of Pehlivan and Mamedov and may be satisfied for the mappings with nonconvex images and for nonconcave functions in the definition of functionals. (C) 2001 Academic Press.
dc.language eng
dc.rights info:eu-repo/semantics/closedAccess
dc.title Statistical cluster points and turnpike theorem in nonconvex problems
dc.type info:eu-repo/semantics/article


Files in this item

Files Size Format View

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record

Search DSpace


Advanced Search

Browse

My Account