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 minlpBB
The solver minlpBB solves large, sparse or dense mixed-integer linear, quadratic and nonlinear programming problems.
 Main features
MINLPbb implements a branch-and-bound algorithm searching a tree whose nodes
correspond to continuous nonlinearly constrained optimization problems.
The continuous problems are solved using filterSQP.
MINLPbb needs second order information for the objective function and the
nonlinear constraints.
TOMLAB estimates any unknown derivatives, but the accuracy and convergence may be worse in such cases.
The dense and the sparse version of MINLPbb
are compiled in two different MEX binaries, making the two versions optimally efficient.
MINLPbb
is integrated with the TOMLAB driver routines.
MINLPbb may be used as subproblem solver in the TOMLAB environment.
 
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