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MISQP
TOMLAB /MISQP provides an interface between The MathWorks' MATLAB and the MISQP solver from Klaus Schittkowski.
MISQP solves general dense mixed-integer nonlinear mathematical programming
problems (MINLP) with equality and inequality constraints.
MISQP solves MINLP 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.
Solver Algorithm
The SQP algorithm is stabilized by a trust region method including Yuan's
second order corrections.
The Hessian of the Lagrangian function is approximated by BFGS updates
subject to the continuous and integer variables.
Successively, mixed-integer quadratic programs must be solved.
For more information about TOMLAB /MISQP see
the TOMLAB /MISQP User's Guide.
For user's guides to all TOMLAB products see the Manual section.
Main features
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Partial derivatives subject to integer variables are approximated internally
at grid points.
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The generated mixed-integer quadratic programming subproblems
must be solved by the code MIQL.
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Separate handling of upper and lower bounds.
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Using boolean, integer, and continuous variables.
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Integer, real and logical option arrays.
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Separate handling of linear constraints.
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Exploiting known partial derivatives subject to integer variables.
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MISQP
may be used as subproblem solver in the TOMLAB
environment.
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