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mipSolve

Solves mixed-integer linear programs (MIP), with dense or sparse Matlab matrices, using a branch-and-bound algorithm by Nemhauser and Wolsey: Integer Programming, chap 8.2, 1989.

Main features

  • The branch-and-bound implementation has three types of tree searching: depth first searching; breadth first searching, and depth first until an integer value solution is found, then breadth searching.
     
  • Priority based variable selection. The user gives a weight for each variable to be used in the variable selection phase.
     
  • The dual LP solver that solves relaxed subproblems is selectable. Using MINOS in Tomlab /MINOS gives rapid solution using MEX-file interfaces.
     
  • A simple knapsack heuristic is implemented, speeding up the solution of knapsack problems.
     
  • The user may give an upper bound on the integer value wanted. Makes it possible to cut branches and avoid node computations.

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