Algorithm 811: NDA: algorithms for nondifferentiable optimization

Authors:
Ladislav Lukšan;Jan Vlček
Affiliations:
Academy of Sciences of the Czech Republic, Prague;Academy of Sciences of the Czech Republic, Prague
Venue:
ACM Transactions on Mathematical Software (TOMS)
Year:
2001

Citing 6
Cited 6

An active set method for solving linearly constrained nonsmooth optimization problems

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Practical methods of optimization; (2nd ed.)

Practical methods of optimization; (2nd ed.)
Proximity control in bundle methods for convex

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Nondifferentiable optimization

Optimization
A bundle-Newton method for nonsmooth unconstrained minimization

Mathematical Programming: Series A and B
Globally convergent variable metric method for convex nonsmooth unconstrained minimization

Journal of Optimization Theory and Applications

Optimal control of flow with discontinuities

Journal of Computational Physics
Exploration of distributional models for a novel intensity-dependent normalization procedure in censored gene expression data

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Codifferential method for minimizing nonsmooth DC functions

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Numerical solution of an adhesion problem with FEM and BEM

Applied Numerical Mathematics
Aggregate codifferential method for nonsmooth DC optimization

Journal of Computational and Applied Mathematics
Global optimization of bounded factorable functions with discontinuities

Journal of Global Optimization

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Abstract

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.