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QLD

Solves convex quadratic programming problems.

Main features

  • QL solves quadratic programming problems with a positive definite objective function matrix and linear equality and inequality constraints.
     
  • The algorithm is an implementation of the dual method of Goldfarb and Idnani and a modification of the original implementation of Powell. Initially, the algorithm computes a solution of the unconstrained problem by performing a Cholesky decomposition and by solving the triangular system. In an iterative way, violated constraints are added to a working set and a minimum with respect to the new subsystem with one additional constraint is calculated. Whenever necessary, a constraint is dropped from the working set. The internal matrix transformations are performed in numerically stable way.
     

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