Minimization of a convex quadratic function subject to separable conical constraints in granular dynamics

Pospíšil, Lukáš, and Dostál, Zdeněk. "Minimization of a convex quadratic function subject to separable conical constraints in granular dynamics." Programs and Algorithms of Numerical Mathematics. Prague: Institute of Mathematics AS CR, 2015. 175-180. <http://eudml.org/doc/269905>.

@inProceedings{Pospíšil2015,
abstract = {The numerical solution of granular dynamics problems with Coulomb friction leads to the problem of minimizing a convex quadratic function with semidefinite Hessian subject to a separable conical constraints. In this paper, we are interested in the numerical solution of this problem. We suggest a modification of an active-set optimal quadratic programming algorithm. The number of projection steps is decreased by using a projected Barzilai-Borwein method. In the numerical experiment, we compare our algorithm with Accelerated Projected Gradient method and Spectral Projected Gradient method on the solution of a particle dynamics problem with hundreds of spherical bodies and static obstacles.},
author = {Pospíšil, Lukáš, Dostál, Zdeněk},
booktitle = {Programs and Algorithms of Numerical Mathematics},
keywords = {constrained optimization; convex quadratic function; granular dynamics; Coulomb friction; modified proportioning with gradient projection; Barzilai-Borwein method},
location = {Prague},
pages = {175-180},
publisher = {Institute of Mathematics AS CR},
title = {Minimization of a convex quadratic function subject to separable conical constraints in granular dynamics},
url = {http://eudml.org/doc/269905},
year = {2015},
}

TY - CLSWK
AU - Pospíšil, Lukáš
AU - Dostál, Zdeněk
TI - Minimization of a convex quadratic function subject to separable conical constraints in granular dynamics
T2 - Programs and Algorithms of Numerical Mathematics
PY - 2015
CY - Prague
PB - Institute of Mathematics AS CR
SP - 175
EP - 180
AB - The numerical solution of granular dynamics problems with Coulomb friction leads to the problem of minimizing a convex quadratic function with semidefinite Hessian subject to a separable conical constraints. In this paper, we are interested in the numerical solution of this problem. We suggest a modification of an active-set optimal quadratic programming algorithm. The number of projection steps is decreased by using a projected Barzilai-Borwein method. In the numerical experiment, we compare our algorithm with Accelerated Projected Gradient method and Spectral Projected Gradient method on the solution of a particle dynamics problem with hundreds of spherical bodies and static obstacles.
KW - constrained optimization; convex quadratic function; granular dynamics; Coulomb friction; modified proportioning with gradient projection; Barzilai-Borwein method
UR - http://eudml.org/doc/269905
ER -