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.
@article{702681,
title = {Minimization of a convex quadratic function subject to separable conical constraints in granular dynamics},
booktitle = {Programs and Algorithms of Numerical Mathematics},
series = {GDML\_Books},
publisher = {Institute of Mathematics AS CR},
address = {Prague},
year = {2015},
pages = {175-180},
url = {http://dml.mathdoc.fr/item/702681}
}
Pospíšil, Lukáš; Dostál, Zdeněk. Minimization of a convex quadratic function subject to separable conical constraints in granular dynamics, dans Programs and Algorithms of Numerical Mathematics, GDML_Books, (2015), pp. 175-180. http://gdmltest.u-ga.fr/item/702681/