TOMLAB Solver Reference
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This page is part of the TOMLAB Manual. See TOMLAB Manual. |
Detailed descriptions of the TOMLAB solvers, driver routines and some utilities are given in the following sections. Also see the M-file help for each solver. All solvers except for the TOMLAB Base Module are described in separate manuals.
For a description of solvers called using the MEX-file interface, see the M-file help, e.g. for the MINOS solver minosTL.m. For more details, see the User's Guide for the particular solver.
clsSolve
Solves dense and sparse nonlinear least squares optimization problems with linear inequality and equality con- straints and simple bounds on the variables.
conSolve
Solve general constrained nonlinear optimization problems.
cutPlane
Solve mixed integer linear programming problems (MIP).
DualSolve
Solve linear programming problems when a dual feasible solution is available.
expSolve
Solve exponential fitting problems for given number of terms p.
glbDirect
Solve box-bounded global optimization problems.
glbSolve
Solve box-bounded global optimization problems.
glcCluster
Solve general constrained mixed-integer global optimization problems using a hybrid algorithm.
glcDirect
Solve global mixed-integer nonlinear programming problems.
glcSolve
Solve general constrained mixed-integer global optimization problems.
infLinSolve
Finds a linearly constrained minimax solution of a function of several variables with the use of any suitable TOMLAB solver. The decision variables may be binary or integer.
infSolve
Find a constrained minimax solution with the use of any suitable TOMLAB solver.
linRatSolve
Finds a linearly constrained solution of a function of the ratio of two linear functions with the use of any suitable TOMLAB solver. Binary and integer variables are not supported.
lpSimplex
Solve general linear programming problems.
L1Solve
Find a constrained L1 solution of a function of several variables with the use of any suitable nonlinear TOMLAB solver.
MilpSolve
Solve mixed integer linear programming problems (MILP).
minlpSolve
Branch & Bound algorithm for Mixed-Integer Nonlinear Programming (MINLP) with convex or nonconvex sub problems using NLP relaxation (Formulated as minlp-IP).
mipSolve
Solve mixed integer linear programming problems (MIP).
multiMin
multiMin solves general constrained mixed-integer global optimization problems. It tries to find all local minima by a multi-start method using a suitable nonlinear programming subsolver.
multiMINLP
multiMINLP solves general constrained mixed-integer global nonlinear optimization problems.
nlpSolve
Solve general constrained nonlinear optimization problems.
pdcoTL
pdcoTL solves linearly constrained convex nonlinear optimization problems.
pdscoTL
pdscoTL solves linearly constrained convex nonlinear optimization problems.
qpSolve
Solve general quadratic programming problems.
slsSolve
Find a Sparse Least Squares (sls) solution to a constrained least squares problem with the use of any suitable TOMLAB NLP solver.
sTrustr
Solve optimization problems constrained by a convex feasible region.
Tfmin
Minimize function of one variable. Find miniumum x in [x_L, x_U] for function Func within tolerance xTol. Solves using Brents minimization algorithm.
Tfzero
Tfzero, TOMLAB fzero routine.
ucSolve
Solve unconstrained nonlinear optimization problems with simple bounds on the variables.
Additional solvers
Documentation for the following solvers is only available at http://tomopt.com and in the m-file help.
- goalSolve - For sparse multi-objective goal attainment problems, with linear and nonlinear constraints.
- Tlsqr - Solves large, sparse linear least squares problem, as well as unsymmetric linear systems.
- lsei - For linearly constrained least squares problem with both equality and inequality constraints.
- Tnnls - Also for linearly constrained least squares problem with both equality and inequality constraints.
- qld - For convex quadratic programming problem.
