Improving the Decomposition of Partially Separable Functions in the Context of Large-Scale Optimization: a First Approach

Andrew R. Conn, Nick Gould and Philippe L. Toint
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Andrew R. Conn: IBM T.J. Watson Research Center
Nick Gould: CERFACS
Philippe L. Toint: FUNDP, Department of Mathematics

A chapter in Large Scale Optimization, 1994, pp 82-94 from Springer

Abstract: Abstract This paper examines the question of modifying the decomposition of a partially separable function in order to improve computational efficiency of large-scale minimization algorithms using a conjugate-gradient inner iteration. The context and motivation are given and the application of a simple strategy discussed on examples extracted from the CUTE test problem collection.

Keywords: exploitation of structure; algorithmic efficiency; partially separable functions (search for similar items in EconPapers)
Date: 1994
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4613-3632-7_5

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DOI: 10.1007/978-1-4613-3632-7_5

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