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minlpBB
The solver minlpBB solves large, sparse or dense mixed-integer linear, quadratic and nonlinear programming problems.
Main features
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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.
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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.
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The dense and the sparse version of MINLPbb
are compiled in two different MEX binaries, making the two versions optimally efficient.
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MINLPbb
is integrated with the TOMLAB driver routines.
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MINLPbb may be used as subproblem solver in the TOMLAB environment.
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