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A superlinearly convergent feasible descent algorithm for nonlinear optimization

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Titel: A superlinearly convergent feasible descent algorithm for nonlinear optimization
Autoren: Jian, Jinbao
Verlagsinformationen: Wuhan University, Wuchang
Schlagwörter: superlinearly convergent feasible descent algorithm, Applications of renewal theory (reliability, demand theory, etc.), Nonlinear programming
Beschreibung: The author considers the following problem: \((p)\) \(\min \{f_0 (x)|x \in R\}\), where \(R = \{x \in E^n |f_i (x) \leq 0\), \(j \in L_1\); \(f_j (x) = 0\), \(j \in L_2\}\), and discusses optimization with nonlinear equality and inequality constraints. The author presents a new algorithm possessing the following properties: (1) The algorithm is a feasible descent method for the expansive problems and the parameter adjusts automatically only for finite time; (2) only one quadratic program needs to be solved at each iteration; (3) It superlinearly converges to the solution of the original problem under some suitable assumption.
Publikationsart: Article
Dateibeschreibung: application/xml
Zugangs-URL: https://zbmath.org/883157
Dokumentencode: edsair.c2b0b933574d..0c8c93bc143425ade3a62a914d217c67
Datenbank: OpenAIRE
Beschreibung
Abstract:The author considers the following problem: \((p)\) \(\min \{f_0 (x)|x \in R\}\), where \(R = \{x \in E^n |f_i (x) \leq 0\), \(j \in L_1\); \(f_j (x) = 0\), \(j \in L_2\}\), and discusses optimization with nonlinear equality and inequality constraints. The author presents a new algorithm possessing the following properties: (1) The algorithm is a feasible descent method for the expansive problems and the parameter adjusts automatically only for finite time; (2) only one quadratic program needs to be solved at each iteration; (3) It superlinearly converges to the solution of the original problem under some suitable assumption.