The NEOS Server offers MINTO for the solution of mixed-integer linear
programs posed in AMPL format.
MINTO (Mixed INT Optimizer) is a mixed integer linear
programming (MILP) solver that implements a branch-and-bound algorithm with
linear programming relaxations. MINTO provides automatic constraint
classification, preprocessing, primal heuristics, and constraint
generation. It has built-in cut generation and can create knapsack cuts, GUB
cuts, clique cuts, implication cuts, flow cuts, mixed integer rounding and
Gomory cuts. The user can customize MINTO by implementing problem-specific
MINTO does not have its own linear programming (LP) solver. This version of
MINTO uses the LP solver
from the Coin-OR project to solve the
The original authors of MINTO are:
Savelsbergh, Georgia Tech, and
Nemhauser, Georgia Tech.
MINTO is currently maintained by Jeff Linderoth,
University of Wisconsin, Madison.
The user must submit a model in AMPL
format. Examples are provided in the examples
section of the AMPL website.
The problem must be specified in a model file. A data file and commands
files may also be provided. If the commands file is specified, it must
contain the AMPL solve command; however, it must not contain
the model or data commands. The model and data
files are renamed internally by NEOS.
The commands file may include option settings for the solver. To specify
solver options, add
option minto_options 'OPTIONS';
The commands file can contain any AMPL command or set options for MINTO.
by modifying the variable 'mintoamp_options'. See the
options page to get a listing of the various options.
A few more items of note specific to the MINTO-AMPL solver