Comparative Study of Two Fast Algorithms for Projecting a Point to the Standard Simplex

Standard

Comparative Study of Two Fast Algorithms for Projecting a Point to the Standard Simplex. / Tamasyan, G. Sh.; Prosolupov, E.V.; Angelov, T. A.

в: Journal of Applied and Industrial Mathematics, Том 10, № 2, 2016, стр. 288-301.

Результаты исследований: Научные публикации в периодических изданиях › статья

BibTeX

@article{9977ea21a304490eaf7a36607d4b93bb,

title = "Comparative Study of Two Fast Algorithms for Projecting a Point to the Standard Simplex",

abstract = "We consider two algorithms for orthogonal projection of a point to the standard simplex. These algorithms are fundamentally different; however, they are related to each other by the following fact: When one of them has the maximum run time, the run time of the other is minimal. Some particular domains are presented whose points are projected by the considered algorithms in the minimum and maximum number of iterations. The correctness of the conclusions is confirmed by the numerical experiments independently implemented in the MatLab environment and the Java programming language.",

keywords = "quadratic programming, projecting a point to a simplex, optimality conditions",

author = "Tamasyan, {G. Sh.} and E.V. Prosolupov and Angelov, {T. A.}",

year = "2016",

doi = "10.1134/S1990478916020137",

language = "English",

volume = "10",

pages = "288--301",

journal = "Journal of Applied and Industrial Mathematics",

issn = "1990-4789",

publisher = "МАИК {"}Наука/Интерпериодика{"}",

number = "2",

}

RIS

TY - JOUR

T1 - Comparative Study of Two Fast Algorithms for Projecting a Point to the Standard Simplex

AU - Tamasyan, G. Sh.

AU - Prosolupov, E.V.

AU - Angelov, T. A.

PY - 2016

Y1 - 2016

N2 - We consider two algorithms for orthogonal projection of a point to the standard simplex. These algorithms are fundamentally different; however, they are related to each other by the following fact: When one of them has the maximum run time, the run time of the other is minimal. Some particular domains are presented whose points are projected by the considered algorithms in the minimum and maximum number of iterations. The correctness of the conclusions is confirmed by the numerical experiments independently implemented in the MatLab environment and the Java programming language.

AB - We consider two algorithms for orthogonal projection of a point to the standard simplex. These algorithms are fundamentally different; however, they are related to each other by the following fact: When one of them has the maximum run time, the run time of the other is minimal. Some particular domains are presented whose points are projected by the considered algorithms in the minimum and maximum number of iterations. The correctness of the conclusions is confirmed by the numerical experiments independently implemented in the MatLab environment and the Java programming language.

KW - quadratic programming

KW - projecting a point to a simplex

KW - optimality conditions

U2 - 10.1134/S1990478916020137

DO - 10.1134/S1990478916020137

M3 - Article

VL - 10

SP - 288

EP - 301

JO - Journal of Applied and Industrial Mathematics

JF - Journal of Applied and Industrial Mathematics

SN - 1990-4789

IS - 2

ER -

ID: 7566975