Nonmonotone Coordinate Search Method for Bound Constrained Optimization

被引：0

作者：

Frau, J. A. ^{[1
]}

Pilotta, E. A. ^{[1
]}

机构：

[1] Univ Nacl Cordoba, Fac Matemat Astron Fis & Comp, CIEM CONICET, Medina Allende S-N,Ciudad Univ, RA-5000 Cordoba, Argentina

来源：

MALAYSIAN JOURNAL OF MATHEMATICAL SCIENCES | 2020年 / 14卷 / 03期

关键词：

Pattern search methods; bound constrained optimization; global convergence; nonmonotone line search; numerical experiments; PATTERN SEARCH; LINE-SEARCH; GLOBAL CONVERGENCE; ALGORITHMS;

D O I：

暂无

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

A new coordinate search method for bound constrained optimization is introduced. The proposed algorithm employs coordinate directions, in a suitable way, with a nonmonotone line search for accepting the new point, without using derivatives of the objective function. The main global convergence results are strongly based on the relationship between the step length and a stationarity measure. Also, a detailed benchmark study comparing different line search strategies is presented using a well known set of test problems.

引用

页码：451 / 471

页数：21

共 32 条

[1] Pattern search methods for user-provided points: Application to molecular geometry problems [J].