Algorithm 1035: A Gradient-based Implementation of the Polyhedral Active Set Algorithm

被引：2

作者：

Hager, William W. ^{[1
]}

Zhang, Hongchao ^{[2
]}

机构：

[1] Univ Florida, Dept Math, POB 118105, Gainesville, FL 32611 USA

[2] Louisiana State Univ, Dept Math, 303 Lockett Hall, Baton Rouge, LA 70803 USA

来源：

ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE | 2023年 / 49卷 / 02期

基金：

美国国家科学基金会;

关键词：

Nonlinear optimization; polyhedral-constrained optimization; active set method; gradient projection method; projection on polyhedron; conjugate gradient method; PASA; PPROJ; CG_DESCENT; NAPHEAP; INTERIOR-POINT ALGORITHM; GLOBAL CONVERGENCE; OPTIMIZATION; DESCENT;

D O I：

10.1145/3583559

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

The Polyhedral Active Set Algorithm (PASA) is designed to optimize a general nonlinear function over a polyhedron. Phase one of the algorithm is a nonmonotone gradient projection algorithm, while phase two is an active set algorithm that explores faces of the constraint polyhedron. A gradient-based implementation is presented, where a projected version of the conjugate gradient algorithm is employed in phase two. Asymptotically, only phase two is performed. Comparisons are given with IPOPT using polyhedral-constrained problems from CUTEst and the Maros/Meszaros quadratic programming test set.

引用

页数：13

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