Competitive Global Optimization Codes
Some Branching Codes Using Function Values Only
DIRECT, Divide Rectangles (in Fortran, by Jörg Gablonsky)
gblSolve, a Matlab 5 implementation of DIRECT
Implementations of a simple and efficient global optimization method
by Jones, Perttunen and Stuckmann for bound constrained problems
DIRECT is based on branching and a Pareto principle for box selection
MCS, Multilevel Coordinate Search (by Huyer and Neumaier)
MCS is based on branching and sequential quadratic programming
A Matlab program for bound constrained global optimization using
function values only
LGO, Lipschitz Global Optimization (commercial, by Janos Pinter)
LGO integrates a suite of global and local scope solvers.
These include branch-and-bound, adaptive random search,
statistical estimation techniques, (penalty-based) unconstrained
and (exact) constrained local optimization methods. See the LGO tutorial
Computational Global Optimization in Nonlinear Systems.
An integrated development environment for global optimization problems
with Lipschitz continuous objective and constraints
Only function values are used; the computed bounds are probabilistic
Some Branch and Bound Codes
BARON, Branch-And-Reduce Optimization Navigator
in Fortran (by Nikos Sahinidis)
``A general purpose solver for optimization problems with nonlinear
constraints and/or integer variables. Fast specialized solvers for
many linearly constrained problems. Easy to use GAMS/AMPL-like
interface to the general purpose and specialized solvers.''
BARON is based on branching and box reduction using convex relaxation
and Lagrange multiplier techniques
alphaBB (by Adjiman, Androulakis, Maranas and Floudas)
alphaBB is based on branching and bound by convex underestimation,
using interval analysis to write nonlinearities in DC (difference of
convexc function) form
Branch and bound code for nonlinear programs
The site has currently the description only; no code
INTOPT_90 ands its sequel
GLOBSOL in Fortran 90 (by Baker Kearfott)
GLobSol is based on branching and box reduction using
interval analysis to verify that a global optimizer cannot be lost.
Branch and bound code for global optimization with general factorable
constraints, with rigorously guaranteed results (even roundoff is
accounted for correctly)
MINLP (by Fletcher and Leyffer)
Branch and bound code for mixed integer nonlinear programming;
finding the global optimum is guaranteed only if all nonintegral
constraints are convex.
The site has currently the description only; no code.
However, problems with AMPL input can be solved online via
MINLP uses standard mixed integer programming techniques and
GAMS/DICOPT (commercial, by Ignacio Grossmann)
No details available about methods used.
Solver for mixed Integer Nonlinear Programming (MINLP) problems.
ILOG Numerica (by Pascal van Hentenryck)
This code was based on branching and box reduction
using interval analysis and constraint satisfaction techniques. ILOG
Numerica is no longer a commercial product. The box reduction and
interval analysis algorithms are now available in
Branch and bound code for constrained optimization (with
mathematically rigorous results)