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Journals / An International Journal of Optimization and Control: Theories & Applications (IJOCTA) / 2013 / Cilt: 3 - Sayı: 2

Modification of the Armijo line search to satisfy the convergence properties of HS method

Mohammed BELLOUFİ
Rachid BENZİNE
Yamina LASKRİ
Pages
145–152
Publication Date
2022-10-11
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Numerical tests are presented tovalidate the different approaches.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The Hestenes-Stiefel (HS) conjugate gradient algorithm is a useful tool of unconstrainednumerical optimization, which has good numerical performance but no global convergence result under traditional line searches.
📊
Key Findings & Data:This paper proposes a line search technique that guarantee the globalconvergence of the Hestenes-Stiefel (HS) conjugate gradient method.
💡
Conclusion & Impact:Numerical tests are presented tovalidate the different approaches.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

The Hestenes-Stiefel (HS) conjugate gradient algorithm is a useful tool of unconstrainednumerical optimization, which has good numerical performance but no global convergence result under traditional line searches. This paper proposes a line search technique that guarantee the globalconvergence of the Hestenes-Stiefel (HS) conjugate gradient method. Numerical tests are presented tovalidate the different approaches.

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Cite This Article

BELLOUFİ, M., BENZİNE, R., LASKRİ, Y. (2022). Modification of the Armijo line search to satisfy the convergence properties of HS method. An International Journal of Optimization and Control: Theories & Applications (IJOCTA), Cilt: 3 - Sayı: 2, 145–152. https://ajindex.com/articles/440736

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