Answers are grounded in this paper and cite their sources.
We present four basic Fortran subroutines for nondifferentiable optimization with simple bounds and general linear constraints. Subroutine PMIN, intended for minimax optimization, is based on a sequential quadratic programming variable metric algorithm. Subroutines PBUN and PNEW, intended for general nonsmooth problems, are based on bundle-type methods. Subroutine PVAR is based on special nonsmooth variable metric methods. Besides the description of methods and codes, we propose computational experiments which demonstrate the efficiency of this approach.
No takes yet. Share an insight, caveat, or question.
Lukšan et al. (2001) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: