The Mosek Interior Point Optimizer for Linear Programming: An Implementation of the Homogeneous Algorithm

  • Erling D. Andersen
  • Knud D. Andersen
Part of the Applied Optimization book series (APOP, volume 33)


The purpose of this work is to present the MOSEK optimizer intended for solution of large-scale sparse linear programs. The optimizer is based on the homogeneous interior-point algorithm which in contrast to the primal-dual algorithm detects a possible primal or dual infeasibility reliably. It employs advanced (parallelized) linear algebra, it handles dense columns in the constraint matrix efficiently, and it has a basis identification procedure.

This paper discusses in details the algorithm and linear algebra em­ployed by the MOSEK interior point optimizer. In particular the ho­mogeneous algorithm is emphasized. Furthermore, extensive computa­tional results are reported. These results include comparative results for the XPRESS simplex and the MOSEK interior point optimizer. Fi­nally, computational results are presented to demonstrate the possible speed-up, when using a parallelized version of the MOSEK interior point optimizer on a multiprocessor Silicon Graphics computer.


Interior Point Dense Column Interior Point Method Cholesky Decomposition Complementary Solution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer Science+Business Media Dordrecht 2000

Authors and Affiliations

  • Erling D. Andersen
  • Knud D. Andersen

There are no affiliations available

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