Volume 15, Issue 4 (1-2019)                   2019, 15(4): 151-170 | Back to browse issues page

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Modarres Khiyabani F, Daneshian B. Symmetric Rank-One Method for Solving Large-Scale Optimization Problems. Journal of Operational Research and Its Applications. 2019; 15 (4) :151-170
URL: http://jamlu.liau.ac.ir/article-1-1511-en.html
Department of Mathematics, Islamic Azad University, Tabriz Branch, Tabriz, Iran
Abstract:   (1804 Views)
The search for finding the local minimization in unconstrained optimization problems and a fixed point of the gradient system of ordinary differential equations are two close problems. Limited-memory algorithms are widely used to solve large-scale problems, while Rang Kuta's methods are also used to solve numerical differential equations. In this paper, using the concept of sub-space method and fixed-step length and integration of line-search and trust-region techniques, an ODE-based hybrid method is proposed for solving large-scale optimization problems. Since the line-search methods may require more iteration for convergence, while Trust-region methods also require a lot of iteration to solve the constrained sub problem, a new class of methods is proposed in this way, which combines the best features of trust-region and line-search methods. The main feature of the proposed method is that the linear equation system is solved only once in order to obtain the experimental step.
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Type of Study: Research | Subject: Special
Received: 2016/12/21 | Accepted: 2017/07/31 | Published: 2019/01/15

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