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Limited Memory Bundle Method

"Just because something doesn't do what you planned it to do doesn't mean it's useless."
- Thomas A. Edison


LMBM is a limited memory bundle method for general, possible nonconvex, nonsmooth (nondifferentiable) large-scale minimization. Both the unconsrained version of the method and the version for bound constrained problems are available.

The software is free for academic teaching and research purposes but I ask you to refer at least one of the references given below if you use it.

Unconstrained Version


tlmbm.f - testprogram for limited memory bundle method.
lmbm.f - limited memory bundle method.
lmsub.f - subroutines for limited memory bundle method.
matcal.f - matrix and vector calculus.
Makefile - makefile.

tnsunc.f - large-scale nonsmooth test problems.

lmbm.tar.gz - all the above in compressed form.
lmbm-mex.tar.gz - MatLab (mex) driver for LMBM.


Bound Constrained Version


tlmbmb.f - testprogram for LMBM-B.
lmbm.f - LMBM-B.
lmbmbs.f - subroutines for LMBM-B.
matca2.f - matrix and vector calculus.
Makefile - makefile.

tnsboc.f - large-scale bound constrained nonsmooth test problems.

lmbmb_v2.tar.gz - all the above in compressed form.

lmbmb_v1_5.tar.gz - older version of LMBM-B in compressed form. This version in not necessary globally convergent. However, in practice, it sometimes works better than the globally convergent version.


Test Problems


tnsunc.f - large unconstrained nonsmooth minimization problems.
tnsboc.f - large bound constrained nonsmooth minimization problems.
tnsiec.f - large inequality constrained nonsmooth minimization problems.

max of quad - some more test problems.



I would like to thank Prof. Marko M. Mäkelä (University of Turku, Finland), Prof. Kaisa Miettinen (University of Jyväskylä, Finland), Prof. Ladislav Luksan (Academy of Sciences of the Czech Republic), and MSc. Seppo Pulkkinen (University of Turku).