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TOMLAB /MIPNLP

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TOMLAB /MIPNLP includes two solvers for nonconvex, convex or pseudo-convex mixed-integer nonlinear programming (MINLP)

Features and capabilities

  • 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.
  • 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.
     
  • The TOMLAB /MIPNLP solvers may be used as subproblem solvers in the TOMLAB environment.
     

Requirements

  • MATLAB 6.5 or later



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