DocumentCode
3029563
Title
Parallel algorithms for unconstrained optimization
Author
Mukai, H.
Author_Institution
Washington University, St. Louis, Missouri, USA
Volume
2
fYear
1979
fDate
12-14 Dec. 1979
Firstpage
451
Lastpage
454
Abstract
In this paper, parallel algorithms are proposed for locating the minimum point of a strictly convex quadratic function. The proposed algorithms are based on a new idea of group conjugacy and they can be considered parallel extensions of conjugate direction methods.
Keywords
Algorithm design and analysis; Concurrent computing; Gradient methods; Minimization methods; Optimization methods; Parallel algorithms;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control including the Symposium on Adaptive Processes, 1979 18th IEEE Conference on
Conference_Location
Fort Lauderdale, FL, USA
Type
conf
DOI
10.1109/CDC.1979.270214
Filename
4046442
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