A family of global convergent inexact secant methods for nonconvex constrained optimization. Issue 2 (June 2018)

• Record Type: Journal Article
• Authors: Wang, Zhujun; Cai, Li; Peng, Zheng
• Is Part Of: Journal of algorithms & computational technology. Volume 12:Issue 2(2018)
• Page Start: 165
• Page End: 176
• Publication Date: 2018-06
• Subjects: Constrained optimization -- secant methods -- nonconvex optimization -- inexact method -- global convergence; Computer algorithms -- Periodicals; Numerical calculations -- Periodicals; Computer algorithms; Numerical calculations; Periodicals; 518.1
• DOI: 10.1177/1748301818762497
• Languages: English
• ISSNs: 1748-3018

Abstract

We present a family of new inexact secant methods in association with Armijo line search technique for solving nonconvex constrained optimization. Different from the existing inexact secant methods, the algorithms proposed in this paper need not compute exact directions. By adopting the nonsmooth exact penalty function as the merit function, the global convergence of the proposed algorithms is established under some reasonable conditions. Some numerical results indicate that the proposed algorithms are both feasible and effective.