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TOMLAB /MIPNLP
TOMLAB /MIPNLP
includes two solvers for
nonconvex, convex or pseudo-convex mixed-integer nonlinear programming (MINLP)
Features and capabilities
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The solver
ecpMINLP
solves convex or pseudo-convex mixed-integer
nonlinear programming problems using an extended cutting plane algorithm
with cuts regulated by a parameter-vector alpha. Cuts and linearizations
are added to MIP subproblem which is then solved by a subsolver in each
iteration.
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The solver algorithm is mainly based on the paper
Solving Pseudo-Convex Mixed Integer Optimization Problems by Cutting Plane Techniques'
Optimization and Engineering 3,
253-280, 2002,
by Tapio Westerlund and Ray Pörn,
but with several modifications.
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The solver
stoaMINLP
is using a Single-search Tree Outer Approximation algorithm
to solve Mixed-Integer NonLinear Programming (MINLP) problems.
Handles both convex or nonconvex problems, but is best suited for solving
convex problems.
If the nonlinear subproblems are known to be convex,
setting an input parameter will make the solver will run much faster.
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TOMLAB /MIPNLP is integrated with the TOMLAB optimization environment.
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The TOMLAB /MIPNLP solvers may be used as subproblem solvers in the TOMLAB
environment.
Requirements
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