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LMBM - FORTRAN Subroutines for Large-Scale Nonsmooth Minimization: User's Manual

Napsu Karmitsa, LMBM - FORTRAN Subroutines for Large-Scale Nonsmooth Minimization: User's Manual. TUCS Technical Reports 856, Turku Centre for Computer Science, 2007.

Abstract:

LMBM is a limited memory bundle method for large-scale nonsmooth, possibly nonconvex, optimization. It is intended for problems that are difficult or even impossible to solve with classical gradient-based optimization methods due to nonsmoothness and for problems that can not be solved efficiently with standard nonsmooth optimization methods (like proximal bundle and bundle trust methods)due to high dimension and/or nonconvexity. LMBM can also be used for solving large smooth problems in which information on the Hessian matrix is difficult to obtain. The algorithm to be described is implemented in FORTRAN77. Beside of the description of the method and the code, some results from numerical experiments are given that demonstrate the efficiency of the algorithm.

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BibTeX entry:

@TECHREPORT{tKarmitsa07a,
  title = {LMBM - FORTRAN Subroutines for Large-Scale Nonsmooth Minimization: User's Manual},
  author = {Karmitsa, Napsu},
  number = {856},
  series = {TUCS Technical Reports},
  publisher = {Turku Centre for Computer Science},
  year = {2007},
  keywords = {Nondifferentiable programming, large-scale optimization, bundle methods, limited memory methods, algorithms.},
  ISBN = {978-952-12-2003-6},
}

Belongs to TUCS Research Unit(s): Other

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