The MOSEK command line tool Version 7.0 (Revision 141)

44 CHAPTER 5. THE OPTIMIZERS FOR CONTINUOUS PROBLEMS
Parameter name
MSK DPAR INTPNT CO TOL PFEAS
MSK DPAR INTPNT CO TOL DFEAS
MSK DPAR INTPNT CO TOL REL GAP
MSK DPAR INTPNT TOL INFEAS
MSK DPAR INTPNT CO TOL MU RED
Purpose
Controls primal feasibility
Controls dual feasibility
Controls relative gap
Controls when the problem is declared infeasible
Controls when the complementarity is reduced enough
Table 5.2: Parameters employed in termination criterion.
5.3 Linear network optimization
5.3.1 Network flow problems
Linear optimization problems with network flow structure can often be solved significantly faster with
a specialized version of the simplex method [7] than with the general solvers.
MOSEK includes a network simplex solver which frequently solves network problems significantly faster
than the standard simplex optimizers.
To use the network simplex optimizer, do the following:
• Input the network flow problem as an ordinary linear optimization problem.
• Set the parameters
– MSK IPAR OPTIMIZER to MSK OPTIMIZER NETWORK PRIMAL SIMPLEX.
MOSEK will automatically detect the network structure and apply the specialized simplex optimizer.
5.4 Conic optimization
5.4.1 The interior-point optimizer
For conic optimization problems only an interior-point type optimizer is available. The interior-point
optimizer is an implementation of the so-called homogeneous and self-dual algorithm. For a detailed
description of the algorithm, please see [8].
5.4.1.1 Interior-point termination criteria
The parameters controlling when the conic interior-point optimizer terminates are shown in Table 5.2.