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14 results for “Unconstrained Optimization”
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Research ArticleOpen accessPhrase in the titleConjugate Gradient ‎Method: A Developed Version to Resolve Unconstrained Optimization ProblemsAhmad Alhawarat, Nguyen-Thoi Trung, Zabidin SallehOne of the important methods that are widely utilized to resolve ‎unconstrained ‎optimization problems is the Conjugate Gradient (CG) method. This paper aims to propose a new version of the CG method on the basis of Weak Wolfe-Powell (WWP) line search. The assumption is bounded below optimization problems with the Lipschitz continuous gradient. The new parameter obtains global convergence properties … …Journal of Computer Science, Vol. 16, Issue 9 · 18 Sep 2020 · 6,887 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleMemoryless Modified Symmetric Rank-One Method for Large-Scale Unconstrained OptimizationFarzin Modarres, Malik Abu Hassan, Wah June LeongProblem statement: Memoryless QN methods have been regarded effective techniques for solving large-scale problems that can be considered as one step limited memory QN methods. In this study, we present a scaled memoryless modified Symmetric Rank-One (SR1) algorithm and investigate the numerical performance of the proposed algorithm for solving large-scale unconstrained optimization problems. Approach: The basic idea is to apply … …American Journal of Applied Sciences, Vol. 6, Issue 12 · 31 Dec 2009 · 7,981 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA New Spectral Conjugate Gradient Method for Nonlinear Unconstrained OptimizationIbtisam A. Masmali, Zabidin Salleh, Ahmad AlhawaratTheconjugate gradient method is widely used to solve large scale unconstrainedoptimization problems. However, the rate of convergence conjugate gradient method is linearunless it restarted. In this study, we present a new spectral conjugategradient modification formula with restart property obtains the globalconvergence and descent properties.In addition, we proposed a new restart condition for Fletcher-Reeves conjugate gradient formula. The numerical resultsdemonstrated that … …Journal of Computer Science, Vol. 17, Issue 6 · 5 Jul 2021 · 6,653 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleAn Alternative Scaling Factor In Broyden's Class Methods for Unconstrained OptimizationMuhammad Fauzi bin Embong, Mustafa bin Mamat, Mohd Rivaie, Ismail bin MohdProblem statement: In order to calculate step size, a suitable line search method can be employed. As the step size usually not exact, the error is unavoidable, thus radically affect quasi-Newton method by as little as 0.1 percent of the step size error. Approach: A suitable scaling factor has to be introduced to overcome this inferiority. Self-scaling Variable Metric algorithms … …Journal of Mathematics and Statistics, Vol. 6, Issue 2 · 2 Jun 2010 · 7,692 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleTwo-Versions of Conjugate Gradient-Algorithms Based on Conjugacy Conditions for Unconstrained OptimizationAbbas Y. AL-Bayati, A.J. Salim, Khalel K. AbboProblem statement: (CG) algorithms, which we had investigated in this study, were widely used in optimization, especially for large scale optimization problems, because it did not need the storage of any matrix. The purpose of this construction was to find new CG-algorithms suitable for solving large scale optimization problems. Approach: Based on pure conjugacy condition and quadratic convex function two … …American Journal of Economics and Business Administration, Vol. 1, Issue 2 · 30 Jun 2009 · 8,108 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Developed Version of Conjugate Gradient Method With a New Parameter for Dai-Liao Conjugacy Condition With an Application to Solar PanelAhmad Alhawarat, Ramadan Sabra, Mehiddin Al-Baali et al.Conjugate Gradient (CG) methods are broadly employed in solving bigger-scale unconstrained optimization problems. Two famous methods are the Hestenes–Stiefel (HS) as well as Polak–Ribière–Polyak (PRP) CG methods, which usually work well in practice. However, they cannot satisfy the Global Convergence (GC) property. To retain and enhance the previous practical behavior as well as rectify the latter difficulty, this paper constructs … …Journal of Computer Science, Vol. 21, Issue 7 · 15 Jul 2025 · 3,147 accessesView PDFCite
Research ArticleOpen accessIn the keywordsGrasshopper Optimization Algorithm-Generative Adversarial Network for Lung Cancer Detection and ClassificationSukruth Gowda, A JayachandranLung cancer is one of the most dangerous deadly diseases for individuals worldwide. Thus, the survival rate is low due to the difficulty in detecting lung cancer at advanced stages like symptoms; thus, prominence for early diagnosis is important. The detection and treatment of lung cancer is having great importance for early diagnosis. The existing Convolution Neural Network (CNN) based … …Journal of Computer Science, Vol. 18, Issue 3 · 9 Apr 2022 · 6,575 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSufficient Descent Condition of the Polak-Ribière-Polyak (PRP) Conjugate Gradient Method without Line SearchAbdelrahman A., KH. I. Osman, Osman O.O. Yousif et al.Nonlinear conjugate gradient methods for unconstrained optimization problems are used in many aspects of theoretical and applied sciences. They are iterative methods, so at any iteration a step length is computed using a method called line search. In most cases, the sufficient descent condition plays an important role to prove the global convergence of a conjugate gradient method. Due to … …Journal of Mathematics and Statistics, Vol. 18, Issue 1 · 14 Mar 2022 · 6,360 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Robust Modification of Hestenes–Stiefel Conjugate Gradient Method with Strong Wolfe Line SearchAwad Abdelrahman, Osman O.O. Yousif, Khalid I. OsmanNonlinear Conjugate Gradient (CG) methods are extensively used for solving large-scale unconstrained optimization problems. Numerous of studies constructed scales and modifications have been conducted recently to improve (CG) methods. In this paper, a simple modified by its conjugate gradient method was proposed. In addition to, established global convergence property and sufficient descent condition, under Strong Wolfe line search. Numerical result … …Journal of Mathematics and Statistics, Vol. 16, Issue 1 · 14 May 2020 · 6,743 accessesView PDFCite
Research ArticleOpen accessIn the keywordsNew Scaled Sufficient Descent Conjugate Gradient Algorithm for Solving Unconstraint Optimization ProblemsAbbas Y. AL-Bayati, Rafiq S. MuhammadProblem statement: The scaled hybrid Conjugate Gradient (CG) algorithm which usually used for solving non-linear functions was presented and was compared with two standard well-Known NAG routines, yielding a new fast comparable algorithm. Approach: We proposed, a new hybrid technique based on the combination of two well-known scaled (CG) formulas for the quadratic model in unconstrained optimization using exact line … …Journal of Computer Science, Vol. 6, Issue 5 · 31 May 2010 · 7,046 accessesView PDFCite