Convergence of Implementable Descent Algorithms for Unconstrained Optimization

被引:0
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作者
J. P. Dussault
机构
[1] Université de Sherbrooke,Département de Mathématiques et Informatique
关键词
descent algorithms; global convergence;
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摘要
Descent algorithms use sufficient descent directions combined with stepsize rules, such as the Armijo rule, to produce sequences of iterates whose cluster points satisfy some necessary optimality conditions. In this note, we present a proof that the whole sequence of iterates converges for quasiconvex objective functions.
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页码:739 / 745
页数:6
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