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In this article, based on the modified secant equation, we propose a modified Hestenes-Stiefel (HS) conjugate gradient method which has similar form as the CG-DESCENT method proposed by Hager and Zhang (SIAM J Optim 16:170–192, 2005). The presented method can generate sufficient descent directions without any line search. Under some mild conditions, we show that it is globally convergent with Armijo line search. Moreover, the R-linear convergence rate of the modified HS method is established. Preliminary numerical results show that the proposed method is promising, and competitive with the well-known CG-DESCENT method.  相似文献
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An accelerated three-term conjugate gradient method is proposed, in which the search direction can satisfy the sufficient descent condition as well as extended Dai–Liao conjugacy condition. Different from the existent methods, a dynamical compensation strategy in our proposed method is considered, that is Li–Fushikuma-type quasi-Newton equation is satisfied as much as possible, otherwise, to some extent, the singular values of iteration matrix of search directions will adaptively clustered, which substantially benefits acceleration the convergence or reduction in the condition number of iteration matrix. Global convergence is established under mild conditions for general objective functions. We also report some numerical results to show its efficiency.  相似文献
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In this note, we aim at improving the proof of Theorem 2.1, 2.2, and Theorem 4.2 in Andrei (J Optim Theory Appl 141:249–264, 2009).  相似文献
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In this article, we propose a new conjugate gradient type formula for computing unconstrained optimization problems. Its form is similar to the original PRP formula and it inherits all nice properties of the PRP method. By utilizing the technique of the three-term PRP method in Zhang [20 L. Zhang , W.J. Zhou , and D.H. Li ( 2006 ). A descent modified Polak-Ribiére-Polyak conjugate gradient method and its global convergence . IMA J. Numer. Anal. 26 : 629640 .[Crossref], [Web of Science ®] [Google Scholar]] and modified PRP method in Yu [17 G.H. Yu ( 2007 ). Nonlinear self-scaling conjugate gradient methods for large-scale optimization problems. Thesis of Doctors Degree, Sun Yat-Sen University . [Google Scholar]], we propose two modified methods of the new formula. The two modified methods all can generate sufficient descent directions which is independent of the line search used. Under some mild conditions, the global convergence and the linearly convergent rate of the two modified methods are established. The numerical results show that the proposed methods are efficient.  相似文献
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