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:: Volume 16, Issue 2 (8-2025) ::
IJOR 2025, 16(2): 63-75 Back to browse issues page
A spectral Conjugate Gradient method for solving unconstrained optimization problems
Mariya Toofan * , Hadi Nasseri
Department of Applied Mathematics, University of Mazandaran, Babolsar, Iran , Mariyatoofan74@gmail.com
Abstract:   (31 Views)
The conjugate gradient method (CGM) stands out as one of the most rapidly growing and effective approaches for addressing unconstrained optimization problems. In recent years, significant efforts have been dedicated to adapting the CGM for tackling nonlinear optimization challenges. This research article introduces a new modification of the Fletcher–Reeves (FR) conjugate gradient projection method. The proposed method is characterized by its sufficient descent property, and its global convergence has been established under specific assumptions. Numerical experiments conducted on a range of functions from the CUTEr collection demonstrate the potential and effectiveness of the proposed methods.
 
Keywords: Nonlinear optimization, line search, spectral conjugate gradient method, suffcient descent property.
Full-Text [PDF 713 kb]   (6 Downloads)    
Type of Study: Original | Subject: Continuous Optimization
Received: 2025/09/30 | Accepted: 2025/12/31 | Published: 2025/12/31
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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 16, Issue 2 (8-2025) Back to browse issues page
مجله انجمن ایرانی تحقیق در عملیات Iranian Journal of Operations Research
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