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Автор Friedlander, Ana
Автор Mario Martínez, José
Автор Raydon, Marcos
Дата выпуска 1995
dc.description In this paper, we present a new method for minimizing a convex quadratic function of many variables with box constraints. The new algorithm is a modification of a method introduced recently by Friedlander and Martinez {SIAM J. on Optimization, February 1994). Following the lines of More and Toraldo (SIAM J. on Optimization 1, pp. 93-113), it combines an efficient unconstrained method with gradient projection techniques. The strategy for “leaving the current face” makes it possible to obtain convergence even when the Hessian is singular. Dual nondegeneracy is not assumed anywhere. The unconstrained minimization algorithm used within the faces was introduced by Barzilai and Borwein and analyzed by Raydan (IMA Journal of Numerical Analysis13, pp. 321-326)
Формат application.pdf
Издатель Gordon and Breach Science Publishers
Копирайт Copyright Taylor and Francis Group, LLC
Тема Quadratic Programming
Тема Bound Constrained Problems
Тема Projected Gradients
Тема Barzilai-Borwein Method
Название A new method for large-scale box constrained convex quadratic minimization problems
Тип research-article
DOI 10.1080/10556789508805602
Electronic ISSN 1029-4937
Print ISSN 1055-6788
Журнал Optimization Methods and Software
Том 5
Первая страница 57
Последняя страница 74
Аффилиация Friedlander, Ana; Department of Applied Mathematics, Uiversity of Campinas
Аффилиация Mario Martínez, José; Department of Applied Mathematics, Uiversity of Campinas
Аффилиация Raydon, Marcos; Department of Mathematics, Central University of Venezuela
Выпуск 1
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