TOMLAB /MISQP
TOMLAB /MISQP integrates The MathWorks' MATLAB and the MISQP and NLPQL solvers from Klaus Schittkowski.
Features and capabilities

The MISQP solver handles dense mixedinteger nonlinear programming problems
by a modified sequential quadratic programming (SQP) method.
Under the assumption that integer variables have a smooth influence on the
model functions, i.e., that function values do not change drastically when
in or decrementing an integer variable, successive quadratic approximations
are applied. It is not assumed that integer variables are relaxable,
i.e., problem functions are evaluated only at integer points.
The code is applicable also to nonconvex optimization problems.

The MIQL solver solves strictly convex mixedinteger quadratic programming
problems subject to linear equality and inequality constraints
by a branchandcut method.

The NLPQLP solver handles dense nonlinear programming problems.

The solver NLPJOB
enables interactive solution of multicriteria optimization problems.
The user can select from several different options.

The solver DFNLP
Solves constrained nonlinear least squares,
L1 and minmax problems, where the objective function is of the following form:
 sum of squares of function values
 sum of absolute function values
 maximum of absolute function values
 maximum of functions
In addition there may be any set of equality or inequality constraints. It is assumed that all individual problem functions are continuously differentiable.
Read more about
DFNLP
at

TOMLAB /MISQP is integrated with the TOMLAB environment.

The TOMLAB /MISQP
solvers may be used as subproblem solvers in the TOMLAB
environment.
Requirements
