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Title: A generalized limited-memory BNS method based on the block BFGS update (English)
Author: Vlček, Jan
Author: Lukšan, Ladislav
Language: English
Journal: Programs and Algorithms of Numerical Mathematics
Volume: Proceedings of Seminar. Janov nad Nisou, June 19-24, 2016
Issue: 2016
Year:
Pages: 164-171
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Category: math
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Summary: A block version of the BFGS variable metric update formula is investigated. It satisfies the quasi-Newton conditions with all used difference vectors and gives the best improvement of convergence in some sense for quadratic objective functions, but it does not guarantee that the direction vectors are descent for general functions. To overcome this difficulty and utilize the advantageous properties of the block BFGS update, a block version of the limited-memory BNS method for large scale unconstrained optimization is proposed. The algorithm is globally convergent for convex sufficiently smooth functions and our numerical experiments indicate its efficiency. (English)
Keyword: unconstrained minimization
Keyword: block variable metric methods
Keyword: limited-memory methods
Keyword: the BFGS update
Keyword: global convergence
Keyword: numerical results
MSC: 65K10
DOI: 10.21136/panm.2016.19
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Date available: 2017-06-20T13:05:22Z
Last updated: 2023-06-05
Stable URL: http://hdl.handle.net/10338.dmlcz/703010
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