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MIQL

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Solver MIQL in TOMLAB /MISQP solves strictly convex mixed-integer quadratic programming problems subject to linear equality and inequality constraints by a branch-and-cut method. The continuous subproblem solutions are obtained by the primal-dual method of Goldfarb and Idnani. The code is designed for solving small to medium size mixed-integer programs.

MIQL is an essential part of the mixed-integer nonlinear programming routine MISQP, MIQL solves the internal mixed-integer quadratic programming subproblems of the SQP-trust-region method.

Solver Algorithm

At the root node of the branch-and-bound search tree, disjunctive and complemented mixed-integer rounding cuts are generated. A branch-and-bound strategy is implemented where different options are available for selecting a branching variable and a free node:

  • maximal fractional branching. Select an integer variable from the solution of the relaxed subproblem with largest distance from next integer value.
     
  • minimal fractional branching. Select an integer variable from the solution of the relaxed subproblem with smallest distance from next integer value.
     
  • Then we search for a free node from where branching, i.e., the generation of two new subproblems, is started:
     
  • best of two. The optimal objective function values of the two child nodes are compared and the node with a lower value is chosen. If both are leafs, i.e., if the corresponding solution is integral, or if the corresponding problem is infeasible or if there is already a better integral solution, strategy best of all is started.
     
  • best of all. Select an integer variable from the solution of the relaxed subproblem with smallest distance from next integer value.
     
  • depth first. Selects a child node whenever possible. If the node is a leaf the best of all strategy is applied.
     
  • The corresponding continuous relaxed problems are solved by the subsolver QL, an implementation of a primal-dual method. The internal matrix transformations are performed in numerically stable way.

    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

  • Separate handling of upper and lower bounds.
     
  • Exploiting dual information for early branching.
     
  • Warm starts
     
  • MIQL may be used as subproblem solver in the TOMLAB environment.
     

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