A family of global convergent inexact secant methods for nonconvex constrained optimization - Details

author：

Wang, Zhujun (Wang, Zhujun.) ^[1] | Cai, Li (Cai, Li.) ^[2] | Peng, Zheng (Peng, Zheng.) ^[3]

Indexed by：

EI Scopus

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.　©　2018,　©　The　Author(s)　2018.

Keyword：

Algorithms Constrained optimization

Community：

[ 1 ] [Wang, Zhujun]College of Science, Hunan Institute of Engineering, Xiangtan, China
[ 2 ] [Cai, Li]Shanghai Research Institute of Microwave Equipment, Shanghai, China
[ 3 ] [Peng, Zheng]College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China