Step-size estimation for unconstrained optimization methods



Document title: Step-size estimation for unconstrained optimization methods
Journal: Computational & applied mathematics
Database: PERIÓDICA
System number: 000269392
ISSN: 1807-0302
Authors: 1
2
Institutions: 1Qufu Normal University, College of Operations Research and Management, Rizhao, Shandong. China
2University of Michigan, Department of Computer and Information Science, Dearborn, Michigan. Estados Unidos de América
Year:
Season: Sep-Dic
Volumen: 24
Number: 3
Pages: 399-416
Country: Brasil
Language: Inglés
Document type: Artículo
Approach: Analítico, descriptivo
English abstract Some computable schemes for descent methods without line search are proposed. Convergence properties are presented. Numerical experiments concerning large scale unconstrained minimization problems are reported
Disciplines: Matemáticas,
Ciencias de la computación
Keyword: Matemáticas aplicadas,
Optimización,
Metodología
Keyword: Mathematics,
Computer science,
Applied mathematics,
Optimization,
Methodology
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