A New Successive Linearization Approach for Solving Nonlinear Programming Problems
Yazarlar (3)
Prof. Dr. Fatma İnci Albayrak Yıldız Teknik Üniversitesi, Türkiye
Dr. Öğr. Üyesi Mustafa Sivri Yıldız Teknik Üniversitesi, Türkiye
Doç. Dr. Gizem Temelcan ERGENECOŞAR İstanbul Aydın Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (ESCI dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | APPLICATIONS AND APPLIED MATHEMATICS-AN INTERNATIONAL JOURNAL | ||
| Dergi ISSN | 1932-9466 | ||
| Dergi Tarandığı Indeksler | ESCI | ||
| Makale Dili | İngilizce | Basım Tarihi | 06-2019 |
| Cilt / Sayı / Sayfa | 14 / 1 / 437–451 | DOI | – |
| Makale Linki | https://digitalcommons.pvamu.edu/aam/vol14/iss1/30/ | ||
| UAK Araştırma Alanları |
Uygulamalı Matematik
|
||
| Özet |
| In this paper, we focused on general nonlinear programming (NLP) problems having m nonlinear (or linear) algebraic inequality (or equality or mixed) constraints with a nonlinear (or linear) algebraic objective function in n variables. We proposed a new two-phase-successive linearization approach for solving NLP problems. Aim of this proposed approach is to find a solution of the NLP problem, based on optimal solution of linear programming (LP) problems, satisfying the nonlinear constraints oversensitively. This approach leads to novel methods. Numerical examples are given to illustrate the approach. |
| Anahtar Kelimeler |
| Nonlinear programming problems | Taylor series | Linear programming problems | Hessian matrix | Maclaurin series | Linearization approach |
