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A globally and superlinearly convergent primal-dual interior point trust region method for large scale constrained optimization.

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Title: A globally and superlinearly convergent primal-dual interior point trust region method for large scale constrained optimization.
Authors: Yamashita, Hiroshi1, hy@msi.co.jp, Yabe, Hiroshi2, yabe@rs.kagu.tus.ac.jp, Tanabe, Takahito1, tanabe@msi.co.jp
Source: Mathematical Programming; Jan2005, Vol. 102 Issue 1, p111-151, 41p, 3 Charts
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 15643827
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: A globally and superlinearly convergent primal-dual interior point trust region method for large scale constrained optimization.
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  Data: <searchLink fieldCode="AU" term="%22Yamashita%2C+Hiroshi%22">Yamashita, Hiroshi</searchLink><relatesTo>1</relatesTo>, <i>hy@msi.co.jp</i><br /><searchLink fieldCode="AU" term="%22Yabe%2C+Hiroshi%22">Yabe, Hiroshi</searchLink><relatesTo>2</relatesTo>, <i>yabe@rs.kagu.tus.ac.jp</i><br /><searchLink fieldCode="AU" term="%22Tanabe%2C+Takahito%22">Tanabe, Takahito</searchLink><relatesTo>1</relatesTo>, <i>tanabe@msi.co.jp</i>
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  Data: <searchLink fieldCode="JN" term="%22Mathematical+Programming%22">Mathematical Programming</searchLink>; Jan2005, Vol. 102 Issue 1, p111-151, 41p, 3 Charts
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      – Type: doi
        Value: 10.1007/s10107-004-0508-9
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      – Code: eng
        Text: English
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        PageCount: 41
        StartPage: 111
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      – TitleFull: A globally and superlinearly convergent primal-dual interior point trust region method for large scale constrained optimization.
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            NameFull: Yamashita, Hiroshi
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            NameFull: Yabe, Hiroshi
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              Text: Jan2005
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              Y: 2005
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              Value: 102
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            – TitleFull: Mathematical Programming
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