On this page:

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 by Seppo Pulkkinen.


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), and Prof. Ladislav Luksan (Academy of Sciences of the Czech Republic).