Solving NLP problems with dynamic system approach based on smoothed penalty function
Yükleniyor...
Dosyalar
Tarih
2009
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Selcuk University Research Center of Applied Mathematics
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
In this work, a dynamical system approach for solving nonlinear programming (NLP) problem based on a smoothed penalty function is investigated. The proposed approach shows that an equilibrium point of the dynamic system is stable and converge to optimal solutions of the corresponding nonlinear programming problem. Furthermore, relationships between optimal solutions for smooth and nonsmooth penalty problem are discussed. Finally, two practical examples are illustrated the applicability of the proposed dynamic system approach with Euler scheme.
Açıklama
Anahtar Kelimeler
Nonlinear programming, Penalty function, Dynamic system, Lyapunov stability, Smoothing method, Doğrusal olmayan programlama, Ceza fonksiyonu, Dinamik sistem, Lyapunov istikrarı, Pürüzsüzleştirme yöntemi
Kaynak
Selcuk Journal of Applied Mathematics
WoS Q Değeri
Scopus Q Değeri
Cilt
10
Sayı
Künye
Özdemir, N., Evirgen, F. (2009). Solving NLP problems with dynamic system approach based on smoothed penalty function. Selcuk Journal of Applied Mathematics, 10 (1), 63-73.
