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

共 50 条

[31] Gradient-Based Worst Case Search Algorithm for Robust Optimization
Chiariello, Andrea G.
Formisano, Alessandro
Martone, Raffaele
Pizzo, Francesco
[J]. IEEE TRANSACTIONS ON MAGNETICS, 2015, 51 (03)
[32] A GRADIENT-BASED ALGORITHM FOR THE STATE INITIALIZATION OF CONTROL-SYSTEMS
CHENG, XJ
HATZIADONIU, C
[J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 1991, 6 (04) : 1349 - 1355
[33] ON THE GRADIENT-BASED ALGORITHM FOR MATRIX FACTORIZATION APPLIED TO DIMENSIONALITY REDUCTION
Nikulin, Vladimir
McLachlan, Geoffrey J.
[J]. BIONFORMATICS 2010: PROCEEDINGS OF THE FIRST INTERNATIONAL CONFERENCE ON BIOINFORMATICS, 2010, : 147 - 152
[34] A Stochastic Gradient-Based Projection Algorithm for Distributed Constrained Optimization
Zhang, Keke
Gao, Shanfu
Chen, Yingjue
Zheng, Zuqing
Lu, Qingguo
[J]. NEURAL INFORMATION PROCESSING, ICONIP 2023, PT I, 2024, 14447 : 356 - 367
[35] A Gradient-based Algorithm for Optimizing Sensing Matrix with Normalization Constraint
Lu, Zeru
Bai, Huang
Sun, Binbin
[J]. PROCEEDINGS OF THE 2016 IEEE 11TH CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA), 2016, : 2376 - 2380
[36] Distributed gradient-based consensus optimization algorithm and convergence analysis
Liang, Shu
Peng, Kaixiang
[J]. Gongcheng Kexue Xuebao/Chinese Journal of Engineering, 2020, 42 (04): : 434 - 440
[37] Enhanced gradient-based algorithm for the estimation of fingerprint orientation fields
Wang, Yi
Hu, Jiankun
Han, Fengling
[J]. APPLIED MATHEMATICS AND COMPUTATION, 2007, 185 (02) : 823 - 833
[38] A supervised gradient-based learning algorithm for optimized entity resolution
Reyes-Galaviz, Orion F.
Pedrycz, Witold
He, Ziyue
Pizzi, Nick J.
[J]. DATA & KNOWLEDGE ENGINEERING, 2017, 112 : 106 - 129
[39] Parallelization of Gradient-based Edge Detection Algorithm on Multicore processors
Atweh, Hanadi Kassem
Hamandi, Lama
Zekri, Ahmed
Zantout, Rached
[J]. 2018 SIXTH INTERNATIONAL CONFERENCE ON DIGITAL INFORMATION, NETWORKING, AND WIRELESS COMMUNICATIONS (DINWC), 2018, : 59 - 64
[40] A Gradient-based Adaptive Nonlocal Means Algorithm for Image Denoising
Zhang, Quan
Luo, Limin
Gui, Zhiguo
Li, Yuanjin
[J]. FIFTH INTERNATIONAL CONFERENCE ON DIGITAL IMAGE PROCESSING (ICDIP 2013), 2013, 8878

← 1 2 3 4 5 →