15.7 Parameters (alphabetical list sorted by type)¶

Double parameters
Integer parameters
String parameters

15.7.1 Double parameters¶

dparam¶: The enumeration type containing all double parameters.

dparam.ana_sol_infeas_tol¶

If a constraint violates its bound with an amount larger than this value, the constraint name, index and violation will be printed by the solution analyzer.

Default: 1e-6
Accepted: [0.0; +inf]
Example: task.putdouparam(dparam.ana_sol_infeas_tol, 1e-6)
Generic name: MSK_DPAR_ANA_SOL_INFEAS_TOL
Groups: Analysis

dparam.basis_rel_tol_s¶

Maximum relative dual bound violation allowed in an optimal basic solution.

Default: 1.0e-12
Accepted: [0.0; +inf]
Example: task.putdouparam(dparam.basis_rel_tol_s, 1.0e-12)
Generic name: MSK_DPAR_BASIS_REL_TOL_S
Groups: Simplex optimizer, Termination criteria

dparam.basis_tol_s¶

Maximum absolute dual bound violation in an optimal basic solution.

Default: 1.0e-6
Accepted: [1.0e-9; +inf]
Example: task.putdouparam(dparam.basis_tol_s, 1.0e-6)
Generic name: MSK_DPAR_BASIS_TOL_S
Groups: Simplex optimizer, Termination criteria

dparam.basis_tol_x¶

Maximum absolute primal bound violation allowed in an optimal basic solution.

Default: 1.0e-6
Accepted: [1.0e-9; +inf]
Example: task.putdouparam(dparam.basis_tol_x, 1.0e-6)
Generic name: MSK_DPAR_BASIS_TOL_X
Groups: Simplex optimizer, Termination criteria

dparam.check_convexity_rel_tol¶

Not in use.

Default: 1e-10
Accepted: [0; +inf]
Example: task.putdouparam(dparam.check_convexity_rel_tol, 1e-10)
Generic name: MSK_DPAR_CHECK_CONVEXITY_REL_TOL
Groups: Interior-point method

dparam.data_sym_mat_tol¶

Absolute zero tolerance for elements in in symmetric matrices. If any value in a symmetric matrix is smaller than this parameter in absolute terms MOSEK will treat the values as zero and generate a warning.

Default: 1.0e-12
Accepted: [1.0e-16; 1.0e-6]
Example: task.putdouparam(dparam.data_sym_mat_tol, 1.0e-12)
Generic name: MSK_DPAR_DATA_SYM_MAT_TOL
Groups: Data check

dparam.data_sym_mat_tol_huge¶

An element in a symmetric matrix which is larger than this value in absolute size causes an error.

Default: 1.0e20
Accepted: [0.0; +inf]
Example: task.putdouparam(dparam.data_sym_mat_tol_huge, 1.0e20)
Generic name: MSK_DPAR_DATA_SYM_MAT_TOL_HUGE
Groups: Data check

dparam.data_sym_mat_tol_large¶

An element in a symmetric matrix which is larger than this value in absolute size causes a warning message to be printed.

Default: 1.0e10
Accepted: [0.0; +inf]
Example: task.putdouparam(dparam.data_sym_mat_tol_large, 1.0e10)
Generic name: MSK_DPAR_DATA_SYM_MAT_TOL_LARGE
Groups: Data check

dparam.data_tol_aij_huge¶

An element in \(A\) which is larger than this value in absolute size causes an error.

Default: 1.0e20
Accepted: [0.0; +inf]
Example: task.putdouparam(dparam.data_tol_aij_huge, 1.0e20)
Generic name: MSK_DPAR_DATA_TOL_AIJ_HUGE
Groups: Data check

dparam.data_tol_aij_large¶

An element in \(A\) which is larger than this value in absolute size causes a warning message to be printed.

Default: 1.0e10
Accepted: [0.0; +inf]
Example: task.putdouparam(dparam.data_tol_aij_large, 1.0e10)
Generic name: MSK_DPAR_DATA_TOL_AIJ_LARGE
Groups: Data check

dparam.data_tol_bound_inf¶

Any bound which in absolute value is greater than this parameter is considered infinite.

Default: 1.0e16
Accepted: [0.0; +inf]
Example: task.putdouparam(dparam.data_tol_bound_inf, 1.0e16)
Generic name: MSK_DPAR_DATA_TOL_BOUND_INF
Groups: Data check

dparam.data_tol_bound_wrn¶

If a bound value is larger than this value in absolute size, then a warning message is issued.

Default: 1.0e8
Accepted: [0.0; +inf]
Example: task.putdouparam(dparam.data_tol_bound_wrn, 1.0e8)
Generic name: MSK_DPAR_DATA_TOL_BOUND_WRN
Groups: Data check

dparam.data_tol_c_huge¶

An element in \(c\) which is larger than the value of this parameter in absolute terms is considered to be huge and generates an error.

Default: 1.0e16
Accepted: [0.0; +inf]
Example: task.putdouparam(dparam.data_tol_c_huge, 1.0e16)
Generic name: MSK_DPAR_DATA_TOL_C_HUGE
Groups: Data check

dparam.data_tol_cj_large¶

An element in \(c\) which is larger than this value in absolute terms causes a warning message to be printed.

Default: 1.0e8
Accepted: [0.0; +inf]
Example: task.putdouparam(dparam.data_tol_cj_large, 1.0e8)
Generic name: MSK_DPAR_DATA_TOL_CJ_LARGE
Groups: Data check

dparam.data_tol_qij¶

Absolute zero tolerance for elements in \(Q\) matrices.

Default: 1.0e-16
Accepted: [0.0; +inf]
Example: task.putdouparam(dparam.data_tol_qij, 1.0e-16)
Generic name: MSK_DPAR_DATA_TOL_QIJ
Groups: Data check

dparam.data_tol_x¶

Zero tolerance for constraints and variables i.e. if the distance between the lower and upper bound is less than this value, then the lower and upper bound is considered identical.

Default: 1.0e-8
Accepted: [0.0; +inf]
Example: task.putdouparam(dparam.data_tol_x, 1.0e-8)
Generic name: MSK_DPAR_DATA_TOL_X
Groups: Data check

dparam.intpnt_co_tol_dfeas¶

Dual feasibility tolerance used by the interior-point optimizer for conic problems.

Default: 1.0e-8
Accepted: [0.0; 1.0]
Example: task.putdouparam(dparam.intpnt_co_tol_dfeas, 1.0e-8)
See also: dparam.intpnt_co_tol_near_rel
Generic name: MSK_DPAR_INTPNT_CO_TOL_DFEAS
Groups: Interior-point method, Termination criteria, Conic interior-point method

dparam.intpnt_co_tol_infeas¶

Infeasibility tolerance used by the interior-point optimizer for conic problems. Controls when the interior-point optimizer declares the model primal or dual infeasible. A small number means the optimizer gets more conservative about declaring the model infeasible.

Default: 1.0e-12
Accepted: [0.0; 1.0]
Example: task.putdouparam(dparam.intpnt_co_tol_infeas, 1.0e-12)
Generic name: MSK_DPAR_INTPNT_CO_TOL_INFEAS
Groups: Interior-point method, Termination criteria, Conic interior-point method

dparam.intpnt_co_tol_mu_red¶

Relative complementarity gap tolerance used by the interior-point optimizer for conic problems.

Default: 1.0e-8
Accepted: [0.0; 1.0]
Example: task.putdouparam(dparam.intpnt_co_tol_mu_red, 1.0e-8)
Generic name: MSK_DPAR_INTPNT_CO_TOL_MU_RED
Groups: Interior-point method, Termination criteria, Conic interior-point method

dparam.intpnt_co_tol_near_rel¶

Optimality tolerance used by the interior-point optimizer for conic problems. If MOSEK cannot compute a solution that has the prescribed accuracy then it will check if the solution found satisfies the termination criteria with all tolerances multiplied by the value of this parameter. If yes, then the solution is also declared optimal.

Default: 1000
Accepted: [1.0; +inf]
Example: task.putdouparam(dparam.intpnt_co_tol_near_rel, 1000)
Generic name: MSK_DPAR_INTPNT_CO_TOL_NEAR_REL
Groups: Interior-point method, Termination criteria, Conic interior-point method

dparam.intpnt_co_tol_pfeas¶

Primal feasibility tolerance used by the interior-point optimizer for conic problems.

Default: 1.0e-8
Accepted: [0.0; 1.0]
Example: task.putdouparam(dparam.intpnt_co_tol_pfeas, 1.0e-8)
See also: dparam.intpnt_co_tol_near_rel
Generic name: MSK_DPAR_INTPNT_CO_TOL_PFEAS
Groups: Interior-point method, Termination criteria, Conic interior-point method

dparam.intpnt_co_tol_rel_gap¶

Relative gap termination tolerance used by the interior-point optimizer for conic problems.

Default: 1.0e-8
Accepted: [0.0; 1.0]
Example: task.putdouparam(dparam.intpnt_co_tol_rel_gap, 1.0e-8)
See also: dparam.intpnt_co_tol_near_rel
Generic name: MSK_DPAR_INTPNT_CO_TOL_REL_GAP
Groups: Interior-point method, Termination criteria, Conic interior-point method

dparam.intpnt_qo_tol_dfeas¶

Dual feasibility tolerance used by the interior-point optimizer for quadratic problems.

Default: 1.0e-8
Accepted: [0.0; 1.0]
Example: task.putdouparam(dparam.intpnt_qo_tol_dfeas, 1.0e-8)
See also: dparam.intpnt_qo_tol_near_rel
Generic name: MSK_DPAR_INTPNT_QO_TOL_DFEAS
Groups: Interior-point method, Termination criteria

dparam.intpnt_qo_tol_infeas¶

Infeasibility tolerance used by the interior-point optimizer for quadratic problems. Controls when the interior-point optimizer declares the model primal or dual infeasible. A small number means the optimizer gets more conservative about declaring the model infeasible.

Default: 1.0e-12
Accepted: [0.0; 1.0]
Example: task.putdouparam(dparam.intpnt_qo_tol_infeas, 1.0e-12)
Generic name: MSK_DPAR_INTPNT_QO_TOL_INFEAS
Groups: Interior-point method, Termination criteria

dparam.intpnt_qo_tol_mu_red¶

Relative complementarity gap tolerance used by the interior-point optimizer for quadratic problems.

Default: 1.0e-8
Accepted: [0.0; 1.0]
Example: task.putdouparam(dparam.intpnt_qo_tol_mu_red, 1.0e-8)
Generic name: MSK_DPAR_INTPNT_QO_TOL_MU_RED
Groups: Interior-point method, Termination criteria

dparam.intpnt_qo_tol_near_rel¶

Optimality tolerance used by the interior-point optimizer for quadratic problems. If MOSEK cannot compute a solution that has the prescribed accuracy then it will check if the solution found satisfies the termination criteria with all tolerances multiplied by the value of this parameter. If yes, then the solution is also declared optimal.

Default: 1000
Accepted: [1.0; +inf]
Example: task.putdouparam(dparam.intpnt_qo_tol_near_rel, 1000)
Generic name: MSK_DPAR_INTPNT_QO_TOL_NEAR_REL
Groups: Interior-point method, Termination criteria

dparam.intpnt_qo_tol_pfeas¶

Primal feasibility tolerance used by the interior-point optimizer for quadratic problems.

Default: 1.0e-8
Accepted: [0.0; 1.0]
Example: task.putdouparam(dparam.intpnt_qo_tol_pfeas, 1.0e-8)
See also: dparam.intpnt_qo_tol_near_rel
Generic name: MSK_DPAR_INTPNT_QO_TOL_PFEAS
Groups: Interior-point method, Termination criteria

dparam.intpnt_qo_tol_rel_gap¶

Relative gap termination tolerance used by the interior-point optimizer for quadratic problems.

Default: 1.0e-8
Accepted: [0.0; 1.0]
Example: task.putdouparam(dparam.intpnt_qo_tol_rel_gap, 1.0e-8)
See also: dparam.intpnt_qo_tol_near_rel
Generic name: MSK_DPAR_INTPNT_QO_TOL_REL_GAP
Groups: Interior-point method, Termination criteria

dparam.intpnt_tol_dfeas¶

Dual feasibility tolerance used by the interior-point optimizer for linear problems.

Default: 1.0e-8
Accepted: [0.0; 1.0]
Example: task.putdouparam(dparam.intpnt_tol_dfeas, 1.0e-8)
Generic name: MSK_DPAR_INTPNT_TOL_DFEAS
Groups: Interior-point method, Termination criteria

dparam.intpnt_tol_dsafe¶

Controls the initial dual starting point used by the interior-point optimizer. If the interior-point optimizer converges slowly and/or the constraint or variable bounds are very large, then it might be worthwhile to increase this value.

Default: 1.0
Accepted: [1.0e-4; +inf]
Example: task.putdouparam(dparam.intpnt_tol_dsafe, 1.0)
Generic name: MSK_DPAR_INTPNT_TOL_DSAFE
Groups: Interior-point method

dparam.intpnt_tol_infeas¶

Infeasibility tolerance used by the interior-point optimizer for linear problems. Controls when the interior-point optimizer declares the model primal or dual infeasible. A small number means the optimizer gets more conservative about declaring the model infeasible.

Default: 1.0e-10
Accepted: [0.0; 1.0]
Example: task.putdouparam(dparam.intpnt_tol_infeas, 1.0e-10)
Generic name: MSK_DPAR_INTPNT_TOL_INFEAS
Groups: Interior-point method, Termination criteria

dparam.intpnt_tol_mu_red¶

Relative complementarity gap tolerance used by the interior-point optimizer for linear problems.

Default: 1.0e-16
Accepted: [0.0; 1.0]
Example: task.putdouparam(dparam.intpnt_tol_mu_red, 1.0e-16)
Generic name: MSK_DPAR_INTPNT_TOL_MU_RED
Groups: Interior-point method, Termination criteria

dparam.intpnt_tol_path¶

Controls how close the interior-point optimizer follows the central path. A large value of this parameter means the central path is followed very closely. On numerically unstable problems it may be worthwhile to increase this parameter.

Default: 1.0e-8
Accepted: [0.0; 0.9999]
Example: task.putdouparam(dparam.intpnt_tol_path, 1.0e-8)
Generic name: MSK_DPAR_INTPNT_TOL_PATH
Groups: Interior-point method

dparam.intpnt_tol_pfeas¶

Primal feasibility tolerance used by the interior-point optimizer for linear problems.

Default: 1.0e-8
Accepted: [0.0; 1.0]
Example: task.putdouparam(dparam.intpnt_tol_pfeas, 1.0e-8)
Generic name: MSK_DPAR_INTPNT_TOL_PFEAS
Groups: Interior-point method, Termination criteria

dparam.intpnt_tol_psafe¶

Controls the initial primal starting point used by the interior-point optimizer. If the interior-point optimizer converges slowly and/or the constraint or variable bounds are very large, then it may be worthwhile to increase this value.

Default: 1.0
Accepted: [1.0e-4; +inf]
Example: task.putdouparam(dparam.intpnt_tol_psafe, 1.0)
Generic name: MSK_DPAR_INTPNT_TOL_PSAFE
Groups: Interior-point method

dparam.intpnt_tol_rel_gap¶

Relative gap termination tolerance used by the interior-point optimizer for linear problems.

Default: 1.0e-8
Accepted: [1.0e-14; +inf]
Example: task.putdouparam(dparam.intpnt_tol_rel_gap, 1.0e-8)
Generic name: MSK_DPAR_INTPNT_TOL_REL_GAP
Groups: Termination criteria, Interior-point method

dparam.intpnt_tol_rel_step¶

Relative step size to the boundary for linear and quadratic optimization problems.

Default: 0.9999
Accepted: [1.0e-4; 0.999999]
Example: task.putdouparam(dparam.intpnt_tol_rel_step, 0.9999)
Generic name: MSK_DPAR_INTPNT_TOL_REL_STEP
Groups: Interior-point method

dparam.intpnt_tol_step_size¶

Minimal step size tolerance. If the step size falls below the value of this parameter, then the interior-point optimizer assumes that it is stalled. In other words the interior-point optimizer does not make any progress and therefore it is better to stop.

Default: 1.0e-6
Accepted: [0.0; 1.0]
Example: task.putdouparam(dparam.intpnt_tol_step_size, 1.0e-6)
Generic name: MSK_DPAR_INTPNT_TOL_STEP_SIZE
Groups: Interior-point method

dparam.lower_obj_cut¶

If either a primal or dual feasible solution is found proving that the optimal objective value is outside the interval \([\) dparam.lower_obj_cut, dparam.upper_obj_cut \(]\), then MOSEK is terminated.

Default: -1.0e30
Accepted: [-inf; +inf]
Example: task.putdouparam(dparam.lower_obj_cut, -1.0e30)
See also: dparam.lower_obj_cut_finite_trh
Generic name: MSK_DPAR_LOWER_OBJ_CUT
Groups: Termination criteria

dparam.lower_obj_cut_finite_trh¶

If the lower objective cut is less than the value of this parameter value, then the lower objective cut i.e. dparam.lower_obj_cut is treated as \(-\infty\).

Default: -0.5e30
Accepted: [-inf; +inf]
Example: task.putdouparam(dparam.lower_obj_cut_finite_trh, -0.5e30)
Generic name: MSK_DPAR_LOWER_OBJ_CUT_FINITE_TRH
Groups: Termination criteria

dparam.mio_djc_max_bigm¶

Maximum allowed big-M value when reformulating disjunctive constraints to linear constraints. Higher values make it more likely that a disjunction is reformulated to linear constraints, but also increase the risk of numerical problems.

Default: 1.0e6
Accepted: [0; +inf]
Example: task.putdouparam(dparam.mio_djc_max_bigm, 1.0e6)
Generic name: MSK_DPAR_MIO_DJC_MAX_BIGM
Groups: Mixed-integer optimization

dparam.mio_max_time¶

This parameter limits the maximum time spent by the mixed-integer optimizer. A negative number means infinity.

Default: -1.0
Accepted: [-inf; +inf]
Example: task.putdouparam(dparam.mio_max_time, -1.0)
Generic name: MSK_DPAR_MIO_MAX_TIME
Groups: Mixed-integer optimization, Termination criteria

dparam.mio_rel_gap_const¶

This value is used to compute the relative gap for the solution to an integer optimization problem.

Default: 1.0e-10
Accepted: [1.0e-15; +inf]
Example: task.putdouparam(dparam.mio_rel_gap_const, 1.0e-10)
Generic name: MSK_DPAR_MIO_REL_GAP_CONST
Groups: Mixed-integer optimization, Termination criteria

dparam.mio_tol_abs_gap¶

Absolute optimality tolerance employed by the mixed-integer optimizer.

Default: 0.0
Accepted: [0.0; +inf]
Example: task.putdouparam(dparam.mio_tol_abs_gap, 0.0)
Generic name: MSK_DPAR_MIO_TOL_ABS_GAP
Groups: Mixed-integer optimization

dparam.mio_tol_abs_relax_int¶

Absolute integer feasibility tolerance. If the distance to the nearest integer is less than this tolerance then an integer constraint is assumed to be satisfied.

Default: 1.0e-5
Accepted: [1e-9; +inf]
Example: task.putdouparam(dparam.mio_tol_abs_relax_int, 1.0e-5)
Generic name: MSK_DPAR_MIO_TOL_ABS_RELAX_INT
Groups: Mixed-integer optimization

dparam.mio_tol_feas¶

Feasibility tolerance for mixed integer solver.

Default: 1.0e-6
Accepted: [1e-9; 1e-3]
Example: task.putdouparam(dparam.mio_tol_feas, 1.0e-6)
Generic name: MSK_DPAR_MIO_TOL_FEAS
Groups: Mixed-integer optimization

dparam.mio_tol_rel_dual_bound_improvement¶

If the relative improvement of the dual bound is smaller than this value, the solver will terminate the root cut generation. A value of 0.0 means that the value is selected automatically.

Default: 0.0
Accepted: [0.0; 1.0]
Example: task.putdouparam(dparam.mio_tol_rel_dual_bound_improvement, 0.0)
Generic name: MSK_DPAR_MIO_TOL_REL_DUAL_BOUND_IMPROVEMENT
Groups: Mixed-integer optimization

dparam.mio_tol_rel_gap¶

Relative optimality tolerance employed by the mixed-integer optimizer.

Default: 1.0e-4
Accepted: [0.0; +inf]
Example: task.putdouparam(dparam.mio_tol_rel_gap, 1.0e-4)
Generic name: MSK_DPAR_MIO_TOL_REL_GAP
Groups: Mixed-integer optimization, Termination criteria

dparam.optimizer_max_ticks¶

CURRENTLY NOT IN USE.

Maximum amount of ticks the optimizer is allowed to spent on the optimization. A negative number means infinity.

Default: -1.0
Accepted: [-inf; +inf]
Example: task.putdouparam(dparam.optimizer_max_ticks, -1.0)
Generic name: MSK_DPAR_OPTIMIZER_MAX_TICKS
Groups: Termination criteria

dparam.optimizer_max_time¶

Maximum amount of time the optimizer is allowed to spent on the optimization. A negative number means infinity.

Default: -1.0
Accepted: [-inf; +inf]
Example: task.putdouparam(dparam.optimizer_max_time, -1.0)
Generic name: MSK_DPAR_OPTIMIZER_MAX_TIME
Groups: Termination criteria

dparam.presolve_tol_abs_lindep¶

Absolute tolerance employed by the linear dependency checker.

Default: 1.0e-6
Accepted: [0.0; +inf]
Example: task.putdouparam(dparam.presolve_tol_abs_lindep, 1.0e-6)
Generic name: MSK_DPAR_PRESOLVE_TOL_ABS_LINDEP
Groups: Presolve

dparam.presolve_tol_aij¶

Absolute zero tolerance employed for \(a_{ij}\) in the presolve.

Default: 1.0e-12
Accepted: [1.0e-15; +inf]
Example: task.putdouparam(dparam.presolve_tol_aij, 1.0e-12)
Generic name: MSK_DPAR_PRESOLVE_TOL_AIJ
Groups: Presolve

dparam.presolve_tol_primal_infeas_perturbation¶

The presolve is allowed to perturb a bound on a constraint or variable by this amount if it removes an infeasibility.

Default: 1.0e-6
Accepted: [0.0; +inf]
Example: task.putdouparam(dparam.presolve_tol_primal_infeas_perturbation, 1.0e-6)
Generic name: MSK_DPAR_PRESOLVE_TOL_PRIMAL_INFEAS_PERTURBATION
Groups: Presolve

dparam.presolve_tol_rel_lindep¶

Relative tolerance employed by the linear dependency checker.

Default: 1.0e-10
Accepted: [0.0; +inf]
Example: task.putdouparam(dparam.presolve_tol_rel_lindep, 1.0e-10)
Generic name: MSK_DPAR_PRESOLVE_TOL_REL_LINDEP
Groups: Presolve

dparam.presolve_tol_s¶

Absolute zero tolerance employed for \(s_i\) in the presolve.

Default: 1.0e-8
Accepted: [0.0; +inf]
Example: task.putdouparam(dparam.presolve_tol_s, 1.0e-8)
Generic name: MSK_DPAR_PRESOLVE_TOL_S
Groups: Presolve

dparam.presolve_tol_x¶

Absolute zero tolerance employed for \(x_j\) in the presolve.

Default: 1.0e-8
Accepted: [0.0; +inf]
Example: task.putdouparam(dparam.presolve_tol_x, 1.0e-8)
Generic name: MSK_DPAR_PRESOLVE_TOL_X
Groups: Presolve

dparam.qcqo_reformulate_rel_drop_tol¶

This parameter determines when columns are dropped in incomplete Cholesky factorization during reformulation of quadratic problems.

Default: 1e-15
Accepted: [0; +inf]
Example: task.putdouparam(dparam.qcqo_reformulate_rel_drop_tol, 1e-15)
Generic name: MSK_DPAR_QCQO_REFORMULATE_REL_DROP_TOL
Groups: Interior-point method

dparam.semidefinite_tol_approx¶

Tolerance to define a matrix to be positive semidefinite.

Default: 1.0e-10
Accepted: [1.0e-15; +inf]
Example: task.putdouparam(dparam.semidefinite_tol_approx, 1.0e-10)
Generic name: MSK_DPAR_SEMIDEFINITE_TOL_APPROX
Groups: Data check

dparam.sim_lu_tol_rel_piv¶

Relative pivot tolerance employed when computing the LU factorization of the basis in the simplex optimizers and in the basis identification procedure. A value closer to 1.0 generally improves numerical stability but typically also implies an increase in the computational work.

Default: 0.01
Accepted: [1.0e-6; 0.999999]
Example: task.putdouparam(dparam.sim_lu_tol_rel_piv, 0.01)
Generic name: MSK_DPAR_SIM_LU_TOL_REL_PIV
Groups: Basis identification, Simplex optimizer

dparam.simplex_abs_tol_piv¶

Absolute pivot tolerance employed by the simplex optimizers.

Default: 1.0e-7
Accepted: [1.0e-12; +inf]
Example: task.putdouparam(dparam.simplex_abs_tol_piv, 1.0e-7)
Generic name: MSK_DPAR_SIMPLEX_ABS_TOL_PIV
Groups: Simplex optimizer

dparam.upper_obj_cut¶

If either a primal or dual feasible solution is found proving that the optimal objective value is outside the interval \([\) dparam.lower_obj_cut, dparam.upper_obj_cut \(]\), then MOSEK is terminated.

Default: 1.0e30
Accepted: [-inf; +inf]
Example: task.putdouparam(dparam.upper_obj_cut, 1.0e30)
See also: dparam.upper_obj_cut_finite_trh
Generic name: MSK_DPAR_UPPER_OBJ_CUT
Groups: Termination criteria

dparam.upper_obj_cut_finite_trh¶

If the upper objective cut is greater than the value of this parameter, then the upper objective cut dparam.upper_obj_cut is treated as \(\infty\).

Default: 0.5e30
Accepted: [-inf; +inf]
Example: task.putdouparam(dparam.upper_obj_cut_finite_trh, 0.5e30)
Generic name: MSK_DPAR_UPPER_OBJ_CUT_FINITE_TRH
Groups: Termination criteria

15.7.2 Integer parameters¶

iparam¶: The enumeration type containing all integer parameters.

iparam.ana_sol_basis¶

Controls whether the basis matrix is analyzed in solution analyzer.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.ana_sol_basis, onoffkey.on.value)
Generic name: MSK_IPAR_ANA_SOL_BASIS
Groups: Analysis

iparam.ana_sol_print_violated¶

A parameter of the problem analyzer. Controls whether a list of violated constraints is printed. All constraints violated by more than the value set by the parameter dparam.ana_sol_infeas_tol will be printed.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.ana_sol_print_violated, onoffkey.off.value)
Generic name: MSK_IPAR_ANA_SOL_PRINT_VIOLATED
Groups: Analysis

iparam.auto_sort_a_before_opt¶

Controls whether the elements in each column of \(A\) are sorted before an optimization is performed. This is not required but makes the optimization more deterministic.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.auto_sort_a_before_opt, onoffkey.off.value)
Generic name: MSK_IPAR_AUTO_SORT_A_BEFORE_OPT
Groups: Debugging

iparam.auto_update_sol_info¶

Controls whether the solution information items are automatically updated after an optimization is performed.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.auto_update_sol_info, onoffkey.off.value)
Generic name: MSK_IPAR_AUTO_UPDATE_SOL_INFO
Groups: Overall system

iparam.basis_solve_use_plus_one¶

If a slack variable is in the basis, then the corresponding column in the basis is a unit vector with -1 in the right position. However, if this parameter is set to onoffkey.on, -1 is replaced by 1.

This has significance for the results returned by the Task.solvewithbasis function.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.basis_solve_use_plus_one, onoffkey.off.value)
Generic name: MSK_IPAR_BASIS_SOLVE_USE_PLUS_ONE
Groups: Simplex optimizer

iparam.bi_clean_optimizer¶

Controls which simplex optimizer is used in the clean-up phase. Anything else than optimizertype.primal_simplex or optimizertype.dual_simplex is equivalent to optimizertype.free_simplex.

Default: free
Accepted: free, intpnt, conic, primal_simplex, dual_simplex, free_simplex, mixed_int (see optimizertype)
Example: task.putintparam(iparam.bi_clean_optimizer, optimizertype.free.value)
Generic name: MSK_IPAR_BI_CLEAN_OPTIMIZER
Groups: Basis identification, Overall solver

iparam.bi_ignore_max_iter¶

If the parameter iparam.intpnt_basis has the value basindtype.no_error and the interior-point optimizer has terminated due to maximum number of iterations, then basis identification is performed if this parameter has the value onoffkey.on.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.bi_ignore_max_iter, onoffkey.off.value)
Generic name: MSK_IPAR_BI_IGNORE_MAX_ITER
Groups: Interior-point method, Basis identification

iparam.bi_ignore_num_error¶

If the parameter iparam.intpnt_basis has the value basindtype.no_error and the interior-point optimizer has terminated due to a numerical problem, then basis identification is performed if this parameter has the value onoffkey.on.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.bi_ignore_num_error, onoffkey.off.value)
Generic name: MSK_IPAR_BI_IGNORE_NUM_ERROR
Groups: Interior-point method, Basis identification

iparam.bi_max_iterations¶

Controls the maximum number of simplex iterations allowed to optimize a basis after the basis identification.

Default: 1000000
Accepted: [0; +inf]
Example: task.putintparam(iparam.bi_max_iterations, 1000000)
Generic name: MSK_IPAR_BI_MAX_ITERATIONS
Groups: Basis identification, Termination criteria

iparam.cache_license¶

Specifies if the license is kept checked out for the lifetime of the MOSEK environment/model/process (onoffkey.on) or returned to the server immediately after the optimization (onoffkey.off).

By default the license is checked out for the lifetime of the MOSEK environment by the first call to Task.optimize.

Check-in and check-out of licenses have an overhead. Frequent communication with the license server should be avoided.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.cache_license, onoffkey.on.value)
Generic name: MSK_IPAR_CACHE_LICENSE
Groups: License manager

iparam.compress_statfile¶

Control compression of stat files.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.compress_statfile, onoffkey.on.value)
Generic name: MSK_IPAR_COMPRESS_STATFILE

iparam.infeas_generic_names¶

Controls whether generic names are used when an infeasible subproblem is created.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.infeas_generic_names, onoffkey.off.value)
Generic name: MSK_IPAR_INFEAS_GENERIC_NAMES
Groups: Infeasibility report

iparam.infeas_prefer_primal¶

If both certificates of primal and dual infeasibility are supplied then only the primal is used when this option is turned on.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.infeas_prefer_primal, onoffkey.on.value)
Generic name: MSK_IPAR_INFEAS_PREFER_PRIMAL
Groups: Overall solver

iparam.infeas_report_auto¶

Controls whether an infeasibility report is automatically produced after the optimization if the problem is primal or dual infeasible.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.infeas_report_auto, onoffkey.off.value)
Generic name: MSK_IPAR_INFEAS_REPORT_AUTO
Groups: Data input/output, Solution input/output

iparam.infeas_report_level¶

Controls the amount of information presented in an infeasibility report. Higher values imply more information.

Default: 1
Accepted: [0; +inf]
Example: task.putintparam(iparam.infeas_report_level, 1)
Generic name: MSK_IPAR_INFEAS_REPORT_LEVEL
Groups: Infeasibility report, Output information

iparam.intpnt_basis¶

Controls whether the interior-point optimizer also computes an optimal basis.

Default: always
Accepted: never, always, no_error, if_feasible, reservered (see basindtype)
Example: task.putintparam(iparam.intpnt_basis, basindtype.always.value)
See also: iparam.bi_ignore_max_iter, iparam.bi_ignore_num_error, iparam.bi_max_iterations, iparam.bi_clean_optimizer
Generic name: MSK_IPAR_INTPNT_BASIS
Groups: Interior-point method, Basis identification

iparam.intpnt_diff_step¶

Controls whether different step sizes are allowed in the primal and dual space.

Default

on

Accepted

on: Different step sizes are allowed.
off: Different step sizes are not allowed.

Example

task.putintparam(iparam.intpnt_diff_step, onoffkey.on.value)

Generic name

MSK_IPAR_INTPNT_DIFF_STEP

Groups

Interior-point method

iparam.intpnt_hotstart¶

Currently not in use.

Default: none
Accepted: none, primal, dual, primal_dual (see intpnthotstart)
Example: task.putintparam(iparam.intpnt_hotstart, intpnthotstart.none.value)
Generic name: MSK_IPAR_INTPNT_HOTSTART
Groups: Interior-point method

iparam.intpnt_max_iterations¶

Controls the maximum number of iterations allowed in the interior-point optimizer.

Default: 400
Accepted: [0; +inf]
Example: task.putintparam(iparam.intpnt_max_iterations, 400)
Generic name: MSK_IPAR_INTPNT_MAX_ITERATIONS
Groups: Interior-point method, Termination criteria

iparam.intpnt_max_num_cor¶

Controls the maximum number of correctors allowed by the multiple corrector procedure. A negative value means that MOSEK is making the choice.

Default: -1
Accepted: [-1; +inf]
Example: task.putintparam(iparam.intpnt_max_num_cor, -1)
Generic name: MSK_IPAR_INTPNT_MAX_NUM_COR
Groups: Interior-point method

iparam.intpnt_max_num_refinement_steps¶

Maximum number of steps to be used by the iterative refinement of the search direction. A negative value implies that the optimizer chooses the maximum number of iterative refinement steps.

Default: -1
Accepted: [-inf; +inf]
Example: task.putintparam(iparam.intpnt_max_num_refinement_steps, -1)
Generic name: MSK_IPAR_INTPNT_MAX_NUM_REFINEMENT_STEPS
Groups: Interior-point method

iparam.intpnt_off_col_trh¶

Controls how many offending columns are detected in the Jacobian of the constraint matrix.

\(0\)	no detection
\(1\)	aggressive detection
\(>1\)	higher values mean less aggressive detection

Default: 40
Accepted: [0; +inf]
Example: task.putintparam(iparam.intpnt_off_col_trh, 40)
Generic name: MSK_IPAR_INTPNT_OFF_COL_TRH
Groups: Interior-point method

iparam.intpnt_order_gp_num_seeds¶

The GP ordering is dependent on a random seed. Therefore, trying several random seeds may lead to a better ordering. This parameter controls the number of random seeds tried.

A value of 0 means that MOSEK makes the choice.

Default: 0
Accepted: [0; +inf]
Example: task.putintparam(iparam.intpnt_order_gp_num_seeds, 0)
Generic name: MSK_IPAR_INTPNT_ORDER_GP_NUM_SEEDS
Groups: Interior-point method

iparam.intpnt_order_method¶

Controls the ordering strategy used by the interior-point optimizer when factorizing the Newton equation system.

Default: free
Accepted: free, appminloc, experimental, try_graphpar, force_graphpar, none (see orderingtype)
Example: task.putintparam(iparam.intpnt_order_method, orderingtype.free.value)
Generic name: MSK_IPAR_INTPNT_ORDER_METHOD
Groups: Interior-point method

iparam.intpnt_purify¶

Currently not in use.

Default: none
Accepted: none, primal, dual, primal_dual, auto (see purify)
Example: task.putintparam(iparam.intpnt_purify, purify.none.value)
Generic name: MSK_IPAR_INTPNT_PURIFY
Groups: Interior-point method

iparam.intpnt_regularization_use¶

Controls whether regularization is allowed.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.intpnt_regularization_use, onoffkey.on.value)
Generic name: MSK_IPAR_INTPNT_REGULARIZATION_USE
Groups: Interior-point method

iparam.intpnt_scaling¶

Controls how the problem is scaled before the interior-point optimizer is used.

Default: free
Accepted: free, none (see scalingtype)
Example: task.putintparam(iparam.intpnt_scaling, scalingtype.free.value)
Generic name: MSK_IPAR_INTPNT_SCALING
Groups: Interior-point method

iparam.intpnt_solve_form¶

Controls whether the primal or the dual problem is solved.

Default: free
Accepted: free, primal, dual (see solveform)
Example: task.putintparam(iparam.intpnt_solve_form, solveform.free.value)
Generic name: MSK_IPAR_INTPNT_SOLVE_FORM
Groups: Interior-point method

iparam.intpnt_starting_point¶

Starting point used by the interior-point optimizer.

Default: free
Accepted: free, guess, constant (see startpointtype)
Example: task.putintparam(iparam.intpnt_starting_point, startpointtype.free.value)
Generic name: MSK_IPAR_INTPNT_STARTING_POINT
Groups: Interior-point method

iparam.license_debug¶

This option is used to turn on debugging of the license manager.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.license_debug, onoffkey.off.value)
Generic name: MSK_IPAR_LICENSE_DEBUG
Groups: License manager

iparam.license_pause_time¶

If iparam.license_wait is onoffkey.on and no license is available, then MOSEK sleeps a number of milliseconds between each check of whether a license has become free.

Default: 100
Accepted: [0; 1000000]
Example: task.putintparam(iparam.license_pause_time, 100)
Generic name: MSK_IPAR_LICENSE_PAUSE_TIME
Groups: License manager

iparam.license_suppress_expire_wrns¶

Controls whether license features expire warnings are suppressed.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.license_suppress_expire_wrns, onoffkey.off.value)
Generic name: MSK_IPAR_LICENSE_SUPPRESS_EXPIRE_WRNS
Groups: License manager, Output information

iparam.license_trh_expiry_wrn¶

If a license feature expires in a numbers of days less than the value of this parameter then a warning will be issued.

Default: 7
Accepted: [0; +inf]
Example: task.putintparam(iparam.license_trh_expiry_wrn, 7)
Generic name: MSK_IPAR_LICENSE_TRH_EXPIRY_WRN
Groups: License manager, Output information

iparam.license_wait¶

If all licenses are in use MOSEK returns with an error code. However, by turning on this parameter MOSEK will wait for an available license.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.license_wait, onoffkey.off.value)
Generic name: MSK_IPAR_LICENSE_WAIT
Groups: Overall solver, Overall system, License manager

iparam.log¶

Controls the amount of log information. The value 0 implies that all log information is suppressed. A higher level implies that more information is logged.

Please note that if a task is employed to solve a sequence of optimization problems the value of this parameter is reduced by the value of iparam.log_cut_second_opt for the second and any subsequent optimizations.

Default: 10
Accepted: [0; +inf]
Example: task.putintparam(iparam.log, 10)
See also: iparam.log_cut_second_opt
Generic name: MSK_IPAR_LOG
Groups: Output information, Logging

iparam.log_ana_pro¶

Controls amount of output from the problem analyzer.

Default: 1
Accepted: [0; +inf]
Example: task.putintparam(iparam.log_ana_pro, 1)
Generic name: MSK_IPAR_LOG_ANA_PRO
Groups: Analysis, Logging

iparam.log_bi¶

Controls the amount of output printed by the basis identification procedure. A higher level implies that more information is logged.

Default: 1
Accepted: [0; +inf]
Example: task.putintparam(iparam.log_bi, 1)
Generic name: MSK_IPAR_LOG_BI
Groups: Basis identification, Output information, Logging

iparam.log_bi_freq¶

Controls how frequently the optimizer outputs information about the basis identification and how frequent the user-defined callback function is called.

Default: 2500
Accepted: [0; +inf]
Example: task.putintparam(iparam.log_bi_freq, 2500)
Generic name: MSK_IPAR_LOG_BI_FREQ
Groups: Basis identification, Output information, Logging

iparam.log_cut_second_opt¶

If a task is employed to solve a sequence of optimization problems, then the value of the log levels is reduced by the value of this parameter. E.g iparam.log and iparam.log_sim are reduced by the value of this parameter for the second and any subsequent optimizations.

Default: 1
Accepted: [0; +inf]
Example: task.putintparam(iparam.log_cut_second_opt, 1)
See also: iparam.log, iparam.log_intpnt, iparam.log_mio, iparam.log_sim
Generic name: MSK_IPAR_LOG_CUT_SECOND_OPT
Groups: Output information, Logging

iparam.log_expand¶

Controls the amount of logging when a data item such as the maximum number constrains is expanded.

Default: 1
Accepted: [0; +inf]
Example: task.putintparam(iparam.log_expand, 1)
Generic name: MSK_IPAR_LOG_EXPAND
Groups: Output information, Logging

iparam.log_feas_repair¶

Controls the amount of output printed when performing feasibility repair. A value higher than one means extensive logging.

Default: 1
Accepted: [0; +inf]
Example: task.putintparam(iparam.log_feas_repair, 1)
Generic name: MSK_IPAR_LOG_FEAS_REPAIR
Groups: Output information, Logging

iparam.log_file¶

If turned on, then some log info is printed when a file is written or read.

Default: 1
Accepted: [0; +inf]
Example: task.putintparam(iparam.log_file, 1)
Generic name: MSK_IPAR_LOG_FILE
Groups: Data input/output, Output information, Logging

iparam.log_include_summary¶

If on, then the solution summary will be printed by Task.optimize, so a separate call to Task.solutionsummary is not necessary.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.log_include_summary, onoffkey.off.value)
Generic name: MSK_IPAR_LOG_INCLUDE_SUMMARY
Groups: Output information, Logging

iparam.log_infeas_ana¶

Controls amount of output printed by the infeasibility analyzer procedures. A higher level implies that more information is logged.

Default: 1
Accepted: [0; +inf]
Example: task.putintparam(iparam.log_infeas_ana, 1)
Generic name: MSK_IPAR_LOG_INFEAS_ANA
Groups: Infeasibility report, Output information, Logging

iparam.log_intpnt¶

Controls amount of output printed by the interior-point optimizer. A higher level implies that more information is logged.

Default: 1
Accepted: [0; +inf]
Example: task.putintparam(iparam.log_intpnt, 1)
Generic name: MSK_IPAR_LOG_INTPNT
Groups: Interior-point method, Output information, Logging

iparam.log_local_info¶

Controls whether local identifying information like environment variables, filenames, IP addresses etc. are printed to the log.

Note that this will only affect some functions. Some functions that specifically emit system information will not be affected.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.log_local_info, onoffkey.on.value)
Generic name: MSK_IPAR_LOG_LOCAL_INFO
Groups: Output information, Logging

iparam.log_mio¶

Controls the log level for the mixed-integer optimizer. A higher level implies that more information is logged.

Default: 4
Accepted: [0; +inf]
Example: task.putintparam(iparam.log_mio, 4)
Generic name: MSK_IPAR_LOG_MIO
Groups: Mixed-integer optimization, Output information, Logging

iparam.log_mio_freq¶

Controls how frequent the mixed-integer optimizer prints the log line. It will print line every time iparam.log_mio_freq relaxations have been solved.

Default: 10
Accepted: [-inf; +inf]
Example: task.putintparam(iparam.log_mio_freq, 10)
Generic name: MSK_IPAR_LOG_MIO_FREQ
Groups: Mixed-integer optimization, Output information, Logging

iparam.log_order¶

If turned on, then factor lines are added to the log.

Default: 1
Accepted: [0; +inf]
Example: task.putintparam(iparam.log_order, 1)
Generic name: MSK_IPAR_LOG_ORDER
Groups: Output information, Logging

iparam.log_presolve¶

Controls amount of output printed by the presolve procedure. A higher level implies that more information is logged.

Default: 1
Accepted: [0; +inf]
Example: task.putintparam(iparam.log_presolve, 1)
Generic name: MSK_IPAR_LOG_PRESOLVE
Groups: Logging

iparam.log_response¶

Controls amount of output printed when response codes are reported. A higher level implies that more information is logged.

Default: 0
Accepted: [0; +inf]
Example: task.putintparam(iparam.log_response, 0)
Generic name: MSK_IPAR_LOG_RESPONSE
Groups: Output information, Logging

iparam.log_sensitivity¶

Controls the amount of logging during the sensitivity analysis.

\(0\). Means no logging information is produced.
\(1\). Timing information is printed.
\(2\). Sensitivity results are printed.

Default: 1
Accepted: [0; +inf]
Example: task.putintparam(iparam.log_sensitivity, 1)
Generic name: MSK_IPAR_LOG_SENSITIVITY
Groups: Output information, Logging

iparam.log_sensitivity_opt¶

Controls the amount of logging from the optimizers employed during the sensitivity analysis. 0 means no logging information is produced.

Default: 0
Accepted: [0; +inf]
Example: task.putintparam(iparam.log_sensitivity_opt, 0)
Generic name: MSK_IPAR_LOG_SENSITIVITY_OPT
Groups: Output information, Logging

iparam.log_sim¶

Controls amount of output printed by the simplex optimizer. A higher level implies that more information is logged.

Default: 4
Accepted: [0; +inf]
Example: task.putintparam(iparam.log_sim, 4)
Generic name: MSK_IPAR_LOG_SIM
Groups: Simplex optimizer, Output information, Logging

iparam.log_sim_freq¶

Controls how frequent the simplex optimizer outputs information about the optimization and how frequent the user-defined callback function is called.

Default: 1000
Accepted: [0; +inf]
Example: task.putintparam(iparam.log_sim_freq, 1000)
Generic name: MSK_IPAR_LOG_SIM_FREQ
Groups: Simplex optimizer, Output information, Logging

iparam.log_sim_minor¶

Currently not in use.

Default: 1
Accepted: [0; +inf]
Example: task.putintparam(iparam.log_sim_minor, 1)
Generic name: MSK_IPAR_LOG_SIM_MINOR
Groups: Simplex optimizer, Output information

iparam.log_storage¶

When turned on, MOSEK prints messages regarding the storage usage and allocation.

Default: 0
Accepted: [0; +inf]
Example: task.putintparam(iparam.log_storage, 0)
Generic name: MSK_IPAR_LOG_STORAGE
Groups: Output information, Overall system, Logging

iparam.max_num_warnings¶

Each warning is shown a limited number of times controlled by this parameter. A negative value is identical to infinite number of times.

Default: 10
Accepted: [-inf; +inf]
Example: task.putintparam(iparam.max_num_warnings, 10)
Generic name: MSK_IPAR_MAX_NUM_WARNINGS
Groups: Output information

iparam.mio_branch_dir¶

Controls whether the mixed-integer optimizer is branching up or down by default.

Default: free
Accepted: free, up, down, near, far, root_lp, guided, pseudocost (see branchdir)
Example: task.putintparam(iparam.mio_branch_dir, branchdir.free.value)
Generic name: MSK_IPAR_MIO_BRANCH_DIR
Groups: Mixed-integer optimization

iparam.mio_conic_outer_approximation¶

If this option is turned on outer approximation is used when solving relaxations of conic problems; otherwise interior point is used.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.mio_conic_outer_approximation, onoffkey.off.value)
Generic name: MSK_IPAR_MIO_CONIC_OUTER_APPROXIMATION
Groups: Mixed-integer optimization

iparam.mio_construct_sol¶

If set to onoffkey.on and all integer variables have been given a value for which a feasible mixed integer solution exists, then MOSEK generates an initial solution to the mixed integer problem by fixing all integer values and solving the remaining problem.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.mio_construct_sol, onoffkey.off.value)
Generic name: MSK_IPAR_MIO_CONSTRUCT_SOL
Groups: Mixed-integer optimization

iparam.mio_cut_clique¶

Controls whether clique cuts should be generated.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.mio_cut_clique, onoffkey.on.value)
Generic name: MSK_IPAR_MIO_CUT_CLIQUE
Groups: Mixed-integer optimization

iparam.mio_cut_cmir¶

Controls whether mixed integer rounding cuts should be generated.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.mio_cut_cmir, onoffkey.on.value)
Generic name: MSK_IPAR_MIO_CUT_CMIR
Groups: Mixed-integer optimization

iparam.mio_cut_gmi¶

Controls whether GMI cuts should be generated.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.mio_cut_gmi, onoffkey.on.value)
Generic name: MSK_IPAR_MIO_CUT_GMI
Groups: Mixed-integer optimization

iparam.mio_cut_implied_bound¶

Controls whether implied bound cuts should be generated.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.mio_cut_implied_bound, onoffkey.on.value)
Generic name: MSK_IPAR_MIO_CUT_IMPLIED_BOUND
Groups: Mixed-integer optimization

iparam.mio_cut_knapsack_cover¶

Controls whether knapsack cover cuts should be generated.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.mio_cut_knapsack_cover, onoffkey.on.value)
Generic name: MSK_IPAR_MIO_CUT_KNAPSACK_COVER
Groups: Mixed-integer optimization

iparam.mio_cut_lipro¶

Controls whether lift-and-project cuts should be generated.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.mio_cut_lipro, onoffkey.off.value)
Generic name: MSK_IPAR_MIO_CUT_LIPRO
Groups: Mixed-integer optimization

iparam.mio_cut_selection_level¶

Controls how aggressively generated cuts are selected to be included in the relaxation.

\(-1\). The optimizer chooses the level of cut selection
\(0\). Generated cuts less likely to be added to the relaxation
\(1\). Cuts are more aggressively selected to be included in the relaxation

Default: -1
Accepted: [-1; +1]
Example: task.putintparam(iparam.mio_cut_selection_level, -1)
Generic name: MSK_IPAR_MIO_CUT_SELECTION_LEVEL
Groups: Mixed-integer optimization

iparam.mio_data_permutation_method¶

Controls what problem data permutation method is appplied to mixed-integer problems.

Default: none
Accepted: none, cyclic_shift, random (see miodatapermmethod)
Example: task.putintparam(iparam.mio_data_permutation_method, miodatapermmethod.none.value)
Generic name: MSK_IPAR_MIO_DATA_PERMUTATION_METHOD
Groups: Mixed-integer optimization

iparam.mio_dual_ray_analysis_level¶

Controls the amount of symmetry detection and handling employed by the mixed-integer optimizer in presolve.

\(-1\). The optimizer chooses the level of dual ray analysis employed
\(0\). Dual ray analysis is disabled
\(1\). A lower amount of dual ray analysis is employed
\(2\). A higher amount of dual ray analysis is employed

Default: -1
Accepted: [-1; 2]
Example: task.putintparam(iparam.mio_dual_ray_analysis_level, -1)
Generic name: MSK_IPAR_MIO_DUAL_RAY_ANALYSIS_LEVEL
Groups: Mixed-integer optimization

iparam.mio_feaspump_level¶

Controls the way the Feasibility Pump heuristic is employed by the mixed-integer optimizer.

\(-1\). The optimizer chooses how the Feasibility Pump is used
\(0\). The Feasibility Pump is disabled
\(1\). The Feasibility Pump is enabled with an effort to improve solution quality
\(2\). The Feasibility Pump is enabled with an effort to reach feasibility early

Default: -1
Accepted: [-1; 2]
Example: task.putintparam(iparam.mio_feaspump_level, -1)
Generic name: MSK_IPAR_MIO_FEASPUMP_LEVEL
Groups: Mixed-integer optimization

iparam.mio_heuristic_level¶

Controls the heuristic employed by the mixed-integer optimizer to locate an initial good integer feasible solution. A value of zero means the heuristic is not used at all. A larger value than \(0\) means that a gradually more sophisticated heuristic is used which is computationally more expensive. A negative value implies that the optimizer chooses the heuristic. Normally a value around \(3\) to \(5\) should be optimal.

Default: -1
Accepted: [-inf; +inf]
Example: task.putintparam(iparam.mio_heuristic_level, -1)
Generic name: MSK_IPAR_MIO_HEURISTIC_LEVEL
Groups: Mixed-integer optimization

iparam.mio_max_num_branches¶

Maximum number of branches allowed during the branch and bound search. A negative value means infinite.

Default: -1
Accepted: [-inf; +inf]
Example: task.putintparam(iparam.mio_max_num_branches, -1)
Generic name: MSK_IPAR_MIO_MAX_NUM_BRANCHES
Groups: Mixed-integer optimization, Termination criteria

iparam.mio_max_num_relaxs¶

Maximum number of relaxations allowed during the branch and bound search. A negative value means infinite.

Default: -1
Accepted: [-inf; +inf]
Example: task.putintparam(iparam.mio_max_num_relaxs, -1)
Generic name: MSK_IPAR_MIO_MAX_NUM_RELAXS
Groups: Mixed-integer optimization

iparam.mio_max_num_restarts¶

Maximum number of restarts allowed during the branch and bound search.

Default: 0
Accepted: [0; +inf]
Example: task.putintparam(iparam.mio_max_num_restarts, 0)
Generic name: MSK_IPAR_MIO_MAX_NUM_RESTARTS
Groups: Mixed-integer optimization

iparam.mio_max_num_root_cut_rounds¶

Maximum number of cut separation rounds at the root node.

Default: 100
Accepted: [0; +inf]
Example: task.putintparam(iparam.mio_max_num_root_cut_rounds, 100)
Generic name: MSK_IPAR_MIO_MAX_NUM_ROOT_CUT_ROUNDS
Groups: Mixed-integer optimization, Termination criteria

iparam.mio_max_num_solutions¶

The mixed-integer optimizer can be terminated after a certain number of different feasible solutions has been located. If this parameter has the value \(n>0\), then the mixed-integer optimizer will be terminated when \(n\) feasible solutions have been located.

Default: -1
Accepted: [-inf; +inf]
Example: task.putintparam(iparam.mio_max_num_solutions, -1)
Generic name: MSK_IPAR_MIO_MAX_NUM_SOLUTIONS
Groups: Mixed-integer optimization, Termination criteria

iparam.mio_memory_emphasis_level¶

Controls how much emphasis is put on reducing memory usage. Being more conservative about memory usage may come at the cost of decreased solution speed.

\(0\). The optimizer chooses
\(1\). More emphasis is put on reducing memory usage and less on speed

Default: 0
Accepted: [0; +1]
Example: task.putintparam(iparam.mio_memory_emphasis_level, 0)
Generic name: MSK_IPAR_MIO_MEMORY_EMPHASIS_LEVEL
Groups: Mixed-integer optimization

iparam.mio_min_rel¶

Number of times a variable must have been branched on for its pseudocost to be considered reliable.

Default: 5
Accepted: [0; +inf]
Example: task.putintparam(iparam.mio_min_rel, 5)
Generic name: MSK_IPAR_MIO_MIN_REL
Groups: Mixed-integer optimization

iparam.mio_mode¶

Controls whether the optimizer includes the integer restrictions and disjunctive constraints when solving a (mixed) integer optimization problem.

Default: satisfied
Accepted: ignored, satisfied (see miomode)
Example: task.putintparam(iparam.mio_mode, miomode.satisfied.value)
Generic name: MSK_IPAR_MIO_MODE
Groups: Overall solver

iparam.mio_node_optimizer¶

Controls which optimizer is employed at the non-root nodes in the mixed-integer optimizer.

Default: free
Accepted: free, intpnt, conic, primal_simplex, dual_simplex, free_simplex, mixed_int (see optimizertype)
Example: task.putintparam(iparam.mio_node_optimizer, optimizertype.free.value)
Generic name: MSK_IPAR_MIO_NODE_OPTIMIZER
Groups: Mixed-integer optimization

iparam.mio_node_selection¶

Controls the node selection strategy employed by the mixed-integer optimizer.

Default: free
Accepted: free, first, best, pseudo (see mionodeseltype)
Example: task.putintparam(iparam.mio_node_selection, mionodeseltype.free.value)
Generic name: MSK_IPAR_MIO_NODE_SELECTION
Groups: Mixed-integer optimization

iparam.mio_numerical_emphasis_level¶

Controls how much emphasis is put on reducing numerical problems possibly at the expense of solution speed.

\(0\). The optimizer chooses
\(1\). More emphasis is put on reducing numerical problems
\(2\). Even more emphasis

Default: 0
Accepted: [0; +2]
Example: task.putintparam(iparam.mio_numerical_emphasis_level, 0)
Generic name: MSK_IPAR_MIO_NUMERICAL_EMPHASIS_LEVEL
Groups: Mixed-integer optimization

iparam.mio_perspective_reformulate¶

Enables or disables perspective reformulation in presolve.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.mio_perspective_reformulate, onoffkey.on.value)
Generic name: MSK_IPAR_MIO_PERSPECTIVE_REFORMULATE
Groups: Mixed-integer optimization

iparam.mio_presolve_aggregator_use¶

Controls if the aggregator should be used.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.mio_presolve_aggregator_use, onoffkey.on.value)
Generic name: MSK_IPAR_MIO_PRESOLVE_AGGREGATOR_USE
Groups: Presolve

iparam.mio_probing_level¶

Controls the amount of probing employed by the mixed-integer optimizer in presolve.

\(-1\). The optimizer chooses the level of probing employed
\(0\). Probing is disabled
\(1\). A low amount of probing is employed
\(2\). A medium amount of probing is employed
\(3\). A high amount of probing is employed

Default: -1
Accepted: [-1; 3]
Example: task.putintparam(iparam.mio_probing_level, -1)
Generic name: MSK_IPAR_MIO_PROBING_LEVEL
Groups: Mixed-integer optimization

iparam.mio_propagate_objective_constraint¶

Use objective domain propagation.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.mio_propagate_objective_constraint, onoffkey.off.value)
Generic name: MSK_IPAR_MIO_PROPAGATE_OBJECTIVE_CONSTRAINT
Groups: Mixed-integer optimization

iparam.mio_qcqo_reformulation_method¶

Controls what reformulation method is applied to mixed-integer quadratic problems.

Default: free
Accepted: free, none, linearization, eigen_val_method, diag_sdp, relax_sdp (see miqcqoreformmethod)
Example: task.putintparam(iparam.mio_qcqo_reformulation_method, miqcqoreformmethod.free.value)
Generic name: MSK_IPAR_MIO_QCQO_REFORMULATION_METHOD
Groups: Mixed-integer optimization

iparam.mio_rins_max_nodes¶

Controls the maximum number of nodes allowed in each call to the RINS heuristic. The default value of -1 means that the value is determined automatically. A value of zero turns off the heuristic.

Default: -1
Accepted: [-1; +inf]
Example: task.putintparam(iparam.mio_rins_max_nodes, -1)
Generic name: MSK_IPAR_MIO_RINS_MAX_NODES
Groups: Mixed-integer optimization

iparam.mio_root_optimizer¶

Controls which optimizer is employed at the root node in the mixed-integer optimizer.

Default: free
Accepted: free, intpnt, conic, primal_simplex, dual_simplex, free_simplex, mixed_int (see optimizertype)
Example: task.putintparam(iparam.mio_root_optimizer, optimizertype.free.value)
Generic name: MSK_IPAR_MIO_ROOT_OPTIMIZER
Groups: Mixed-integer optimization

iparam.mio_root_repeat_presolve_level¶

Controls whether presolve can be repeated at root node.

\(-1\). The optimizer chooses whether presolve is repeated
\(0\). Never repeat presolve
\(1\). Always repeat presolve

Default: -1
Accepted: [-1; 1]
Example: task.putintparam(iparam.mio_root_repeat_presolve_level, -1)
Generic name: MSK_IPAR_MIO_ROOT_REPEAT_PRESOLVE_LEVEL
Groups: Mixed-integer optimization

iparam.mio_seed¶

Sets the random seed used for randomization in the mixed integer optimizer. Selecting a different seed can change the path the optimizer takes to the optimal solution.

Default: 42
Accepted: [0; +inf]
Example: task.putintparam(iparam.mio_seed, 42)
Generic name: MSK_IPAR_MIO_SEED
Groups: Mixed-integer optimization

iparam.mio_symmetry_level¶

Controls the amount of symmetry detection and handling employed by the mixed-integer optimizer in presolve.

\(-1\). The optimizer chooses the level of symmetry detection and handling employed
\(0\). Symmetry detection and handling is disabled
\(1\). A low amount of symmetry detection and handling is employed
\(2\). A medium amount of symmetry detection and handling is employed
\(3\). A high amount of symmetry detection and handling is employed
\(4\). An extremely high amount of symmetry detection and handling is employed

Default: -1
Accepted: [-1; 4]
Example: task.putintparam(iparam.mio_symmetry_level, -1)
Generic name: MSK_IPAR_MIO_SYMMETRY_LEVEL
Groups: Mixed-integer optimization

iparam.mio_var_selection¶

Controls the variable selection strategy employed by the mixed-integer optimizer.

Default: free
Accepted: free, pseudocost, strong (see miovarseltype)
Example: task.putintparam(iparam.mio_var_selection, miovarseltype.free.value)
Generic name: MSK_IPAR_MIO_VAR_SELECTION
Groups: Mixed-integer optimization

iparam.mio_vb_detection_level¶

Controls how much effort is put into detecting variable bounds.

\(-1\). The optimizer chooses
\(0\). No variable bounds are detected
\(1\). Only detect variable bounds that are directly represented in the problem
\(2\). Detect variable bounds in probing

Default: -1
Accepted: [-1; +2]
Example: task.putintparam(iparam.mio_vb_detection_level, -1)
Generic name: MSK_IPAR_MIO_VB_DETECTION_LEVEL
Groups: Mixed-integer optimization

iparam.mt_spincount¶

Set the number of iterations to spin before sleeping.

Default: 0
Accepted: [0; 1000000000]
Example: task.putintparam(iparam.mt_spincount, 0)
Generic name: MSK_IPAR_MT_SPINCOUNT
Groups: Overall system

iparam.ng¶

Not in use.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.ng, onoffkey.off.value)
Generic name: MSK_IPAR_NG

iparam.num_threads¶

Controls the number of threads employed by the optimizer. If set to 0 the number of threads used will be equal to the number of cores detected on the machine.

Default: 0
Accepted: [0; +inf]
Example: task.putintparam(iparam.num_threads, 0)
Generic name: MSK_IPAR_NUM_THREADS
Groups: Overall system

iparam.opf_write_header¶

Write a text header with date and MOSEK version in an OPF file.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.opf_write_header, onoffkey.on.value)
Generic name: MSK_IPAR_OPF_WRITE_HEADER
Groups: Data input/output

iparam.opf_write_hints¶

Write a hint section with problem dimensions in the beginning of an OPF file.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.opf_write_hints, onoffkey.on.value)
Generic name: MSK_IPAR_OPF_WRITE_HINTS
Groups: Data input/output

iparam.opf_write_line_length¶

Aim to keep lines in OPF files not much longer than this.

Default: 80
Accepted: [0; +inf]
Example: task.putintparam(iparam.opf_write_line_length, 80)
Generic name: MSK_IPAR_OPF_WRITE_LINE_LENGTH
Groups: Data input/output

iparam.opf_write_parameters¶

Write a parameter section in an OPF file.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.opf_write_parameters, onoffkey.off.value)
Generic name: MSK_IPAR_OPF_WRITE_PARAMETERS
Groups: Data input/output

iparam.opf_write_problem¶

Write objective, constraints, bounds etc. to an OPF file.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.opf_write_problem, onoffkey.on.value)
Generic name: MSK_IPAR_OPF_WRITE_PROBLEM
Groups: Data input/output

iparam.opf_write_sol_bas¶

If iparam.opf_write_solutions is onoffkey.on and a basic solution is defined, include the basic solution in OPF files.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.opf_write_sol_bas, onoffkey.on.value)
Generic name: MSK_IPAR_OPF_WRITE_SOL_BAS
Groups: Data input/output

iparam.opf_write_sol_itg¶

If iparam.opf_write_solutions is onoffkey.on and an integer solution is defined, write the integer solution in OPF files.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.opf_write_sol_itg, onoffkey.on.value)
Generic name: MSK_IPAR_OPF_WRITE_SOL_ITG
Groups: Data input/output

iparam.opf_write_sol_itr¶

If iparam.opf_write_solutions is onoffkey.on and an interior solution is defined, write the interior solution in OPF files.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.opf_write_sol_itr, onoffkey.on.value)
Generic name: MSK_IPAR_OPF_WRITE_SOL_ITR
Groups: Data input/output

iparam.opf_write_solutions¶

Enable inclusion of solutions in the OPF files.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.opf_write_solutions, onoffkey.off.value)
Generic name: MSK_IPAR_OPF_WRITE_SOLUTIONS
Groups: Data input/output

iparam.optimizer¶

The parameter controls which optimizer is used to optimize the task.

Default: free
Accepted: free, intpnt, conic, primal_simplex, dual_simplex, free_simplex, mixed_int (see optimizertype)
Example: task.putintparam(iparam.optimizer, optimizertype.free.value)
Generic name: MSK_IPAR_OPTIMIZER
Groups: Overall solver

iparam.param_read_case_name¶

If turned on, then names in the parameter file are case sensitive.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.param_read_case_name, onoffkey.on.value)
Generic name: MSK_IPAR_PARAM_READ_CASE_NAME
Groups: Data input/output

iparam.param_read_ign_error¶

If turned on, then errors in parameter settings is ignored.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.param_read_ign_error, onoffkey.off.value)
Generic name: MSK_IPAR_PARAM_READ_IGN_ERROR
Groups: Data input/output

iparam.presolve_eliminator_max_fill¶

Controls the maximum amount of fill-in that can be created by one pivot in the elimination phase of the presolve. A negative value means the parameter value is selected automatically.

Default: -1
Accepted: [-inf; +inf]
Example: task.putintparam(iparam.presolve_eliminator_max_fill, -1)
Generic name: MSK_IPAR_PRESOLVE_ELIMINATOR_MAX_FILL
Groups: Presolve

iparam.presolve_eliminator_max_num_tries¶

Control the maximum number of times the eliminator is tried. A negative value implies MOSEK decides.

Default: -1
Accepted: [-inf; +inf]
Example: task.putintparam(iparam.presolve_eliminator_max_num_tries, -1)
Generic name: MSK_IPAR_PRESOLVE_ELIMINATOR_MAX_NUM_TRIES
Groups: Presolve

iparam.presolve_level¶

Currently not used.

Default: -1
Accepted: [-inf; +inf]
Example: task.putintparam(iparam.presolve_level, -1)
Generic name: MSK_IPAR_PRESOLVE_LEVEL
Groups: Overall solver, Presolve

iparam.presolve_lindep_abs_work_trh¶

Controls linear dependency check in presolve. The linear dependency check is potentially computationally expensive.

Default: 100
Accepted: [-inf; +inf]
Example: task.putintparam(iparam.presolve_lindep_abs_work_trh, 100)
Generic name: MSK_IPAR_PRESOLVE_LINDEP_ABS_WORK_TRH
Groups: Presolve

iparam.presolve_lindep_new¶

Controls whether whether a new experimental linear dependency checker is employed.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.presolve_lindep_new, onoffkey.off.value)
Generic name: MSK_IPAR_PRESOLVE_LINDEP_NEW
Groups: Presolve

iparam.presolve_lindep_rel_work_trh¶

Controls linear dependency check in presolve. The linear dependency check is potentially computationally expensive.

Default: 100
Accepted: [-inf; +inf]
Example: task.putintparam(iparam.presolve_lindep_rel_work_trh, 100)
Generic name: MSK_IPAR_PRESOLVE_LINDEP_REL_WORK_TRH
Groups: Presolve

iparam.presolve_lindep_use¶

Controls whether the linear constraints are checked for linear dependencies.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.presolve_lindep_use, onoffkey.on.value)
Generic name: MSK_IPAR_PRESOLVE_LINDEP_USE
Groups: Presolve

iparam.presolve_max_num_pass¶

Control the maximum number of times presolve passes over the problem. A negative value implies MOSEK decides.

Default: -1
Accepted: [-inf; +inf]
Example: task.putintparam(iparam.presolve_max_num_pass, -1)
Generic name: MSK_IPAR_PRESOLVE_MAX_NUM_PASS
Groups: Presolve

iparam.presolve_max_num_reductions¶

Controls the maximum number of reductions performed by the presolve. The value of the parameter is normally only changed in connection with debugging. A negative value implies that an infinite number of reductions are allowed.

Default: -1
Accepted: [-inf; +inf]
Example: task.putintparam(iparam.presolve_max_num_reductions, -1)
Generic name: MSK_IPAR_PRESOLVE_MAX_NUM_REDUCTIONS
Groups: Overall solver, Presolve

iparam.presolve_use¶

Controls whether the presolve is applied to a problem before it is optimized.

Default: free
Accepted: off, on, free (see presolvemode)
Example: task.putintparam(iparam.presolve_use, presolvemode.free.value)
Generic name: MSK_IPAR_PRESOLVE_USE
Groups: Overall solver, Presolve

iparam.primal_repair_optimizer¶

Controls which optimizer that is used to find the optimal repair.

Default: free
Accepted: free, intpnt, conic, primal_simplex, dual_simplex, free_simplex, mixed_int (see optimizertype)
Example: task.putintparam(iparam.primal_repair_optimizer, optimizertype.free.value)
Generic name: MSK_IPAR_PRIMAL_REPAIR_OPTIMIZER
Groups: Overall solver

iparam.ptf_write_parameters¶

If iparam.ptf_write_parameters is onoffkey.on, the parameters section is written.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.ptf_write_parameters, onoffkey.off.value)
Generic name: MSK_IPAR_PTF_WRITE_PARAMETERS
Groups: Data input/output

iparam.ptf_write_solutions¶

If iparam.ptf_write_solutions is onoffkey.on, the solution section is written if any solutions are available, otherwise solution section is not written even if solutions are available.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.ptf_write_solutions, onoffkey.off.value)
Generic name: MSK_IPAR_PTF_WRITE_SOLUTIONS
Groups: Data input/output

iparam.ptf_write_transform¶

If iparam.ptf_write_transform is onoffkey.on, constraint blocks with identifiable conic slacks are transformed into conic constraints and the slacks are eliminated.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.ptf_write_transform, onoffkey.on.value)
Generic name: MSK_IPAR_PTF_WRITE_TRANSFORM
Groups: Data input/output

iparam.read_debug¶

Turns on additional debugging information when reading files.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.read_debug, onoffkey.off.value)
Generic name: MSK_IPAR_READ_DEBUG
Groups: Data input/output

iparam.read_keep_free_con¶

Controls whether the free constraints are included in the problem.

Default

off

Accepted

on: The free constraints are kept.
off: The free constraints are discarded.

Example

task.putintparam(iparam.read_keep_free_con, onoffkey.off.value)

Generic name

MSK_IPAR_READ_KEEP_FREE_CON

Groups

Data input/output

iparam.read_mps_format¶

Controls how strictly the MPS file reader interprets the MPS format.

Default: free
Accepted: strict, relaxed, free, cplex (see mpsformat)
Example: task.putintparam(iparam.read_mps_format, mpsformat.free.value)
Generic name: MSK_IPAR_READ_MPS_FORMAT
Groups: Data input/output

iparam.read_mps_width¶

Controls the maximal number of characters allowed in one line of the MPS file.

Default: 1024
Accepted: [80; +inf]
Example: task.putintparam(iparam.read_mps_width, 1024)
Generic name: MSK_IPAR_READ_MPS_WIDTH
Groups: Data input/output

iparam.read_task_ignore_param¶

Controls whether MOSEK should ignore the parameter setting defined in the task file and use the default parameter setting instead.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.read_task_ignore_param, onoffkey.off.value)
Generic name: MSK_IPAR_READ_TASK_IGNORE_PARAM
Groups: Data input/output

iparam.remote_use_compression¶

Use compression when sending data to an optimization server.

Default: zstd
Accepted: none, free, gzip, zstd (see compresstype)
Example: task.putintparam(iparam.remote_use_compression, compresstype.zstd.value)
Generic name: MSK_IPAR_REMOTE_USE_COMPRESSION

iparam.remove_unused_solutions¶

Removes unused solutions before the optimization is performed.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.remove_unused_solutions, onoffkey.off.value)
Generic name: MSK_IPAR_REMOVE_UNUSED_SOLUTIONS
Groups: Overall system

iparam.sensitivity_all¶

If set to onoffkey.on, then Task.sensitivityreport analyzes all bounds and variables instead of reading a specification from the file.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.sensitivity_all, onoffkey.off.value)
Generic name: MSK_IPAR_SENSITIVITY_ALL
Groups: Overall solver

iparam.sensitivity_optimizer¶

Controls which optimizer is used for optimal partition sensitivity analysis.

Default: free_simplex
Accepted: free, intpnt, conic, primal_simplex, dual_simplex, free_simplex, mixed_int (see optimizertype)
Example: task.putintparam(iparam.sensitivity_optimizer, optimizertype.free_simplex.value)
Generic name: MSK_IPAR_SENSITIVITY_OPTIMIZER
Groups: Overall solver, Simplex optimizer

iparam.sensitivity_type¶

Controls which type of sensitivity analysis is to be performed.

Default: basis
Accepted: basis (see sensitivitytype)
Example: task.putintparam(iparam.sensitivity_type, sensitivitytype.basis.value)
Generic name: MSK_IPAR_SENSITIVITY_TYPE
Groups: Overall solver

iparam.sim_basis_factor_use¶

Controls whether an LU factorization of the basis is used in a hot-start. Forcing a refactorization sometimes improves the stability of the simplex optimizers, but in most cases there is a performance penalty.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.sim_basis_factor_use, onoffkey.on.value)
Generic name: MSK_IPAR_SIM_BASIS_FACTOR_USE
Groups: Simplex optimizer

iparam.sim_degen¶

Controls how aggressively degeneration is handled.

Default: free
Accepted: none, free, aggressive, moderate, minimum (see simdegen)
Example: task.putintparam(iparam.sim_degen, simdegen.free.value)
Generic name: MSK_IPAR_SIM_DEGEN
Groups: Simplex optimizer

iparam.sim_detect_pwl¶

Not in use.

Default

on

Accepted

on: PWL are detected.
off: PWL are not detected.

Example

task.putintparam(iparam.sim_detect_pwl, onoffkey.on.value)

Generic name

MSK_IPAR_SIM_DETECT_PWL

Groups

Simplex optimizer

iparam.sim_dual_crash¶

Controls whether crashing is performed in the dual simplex optimizer. If this parameter is set to \(x\), then a crash will be performed if a basis consists of more than \((100-x)\mod f_v\) entries, where \(f_v\) is the number of fixed variables.

Default: 90
Accepted: [0; +inf]
Example: task.putintparam(iparam.sim_dual_crash, 90)
Generic name: MSK_IPAR_SIM_DUAL_CRASH
Groups: Dual simplex

iparam.sim_dual_phaseone_method¶

An experimental feature.

Default: 0
Accepted: [0; 10]
Example: task.putintparam(iparam.sim_dual_phaseone_method, 0)
Generic name: MSK_IPAR_SIM_DUAL_PHASEONE_METHOD
Groups: Simplex optimizer

iparam.sim_dual_restrict_selection¶

The dual simplex optimizer can use a so-called restricted selection/pricing strategy to choose the outgoing variable. Hence, if restricted selection is applied, then the dual simplex optimizer first choose a subset of all the potential outgoing variables. Next, for some time it will choose the outgoing variable only among the subset. From time to time the subset is redefined. A larger value of this parameter implies that the optimizer will be more aggressive in its restriction strategy, i.e. a value of 0 implies that the restriction strategy is not applied at all.

Default: 50
Accepted: [0; 100]
Example: task.putintparam(iparam.sim_dual_restrict_selection, 50)
Generic name: MSK_IPAR_SIM_DUAL_RESTRICT_SELECTION
Groups: Dual simplex

iparam.sim_dual_selection¶

Controls the choice of the incoming variable, known as the selection strategy, in the dual simplex optimizer.

Default: free
Accepted: free, full, ase, devex, se, partial (see simseltype)
Example: task.putintparam(iparam.sim_dual_selection, simseltype.free.value)
Generic name: MSK_IPAR_SIM_DUAL_SELECTION
Groups: Dual simplex

iparam.sim_exploit_dupvec¶

Controls if the simplex optimizers are allowed to exploit duplicated columns.

Default: off
Accepted: on, off, free (see simdupvec)
Example: task.putintparam(iparam.sim_exploit_dupvec, simdupvec.off.value)
Generic name: MSK_IPAR_SIM_EXPLOIT_DUPVEC
Groups: Simplex optimizer

iparam.sim_hotstart¶

Controls the type of hot-start that the simplex optimizer perform.

Default: free
Accepted: none, free, status_keys (see simhotstart)
Example: task.putintparam(iparam.sim_hotstart, simhotstart.free.value)
Generic name: MSK_IPAR_SIM_HOTSTART
Groups: Simplex optimizer

iparam.sim_hotstart_lu¶

Determines if the simplex optimizer should exploit the initial factorization.

Default

on

Accepted

on: Factorization is reused if possible.
off: Factorization is recomputed.

Example

task.putintparam(iparam.sim_hotstart_lu, onoffkey.on.value)

Generic name

MSK_IPAR_SIM_HOTSTART_LU

Groups

Simplex optimizer

iparam.sim_max_iterations¶

Maximum number of iterations that can be used by a simplex optimizer.

Default: 10000000
Accepted: [0; +inf]
Example: task.putintparam(iparam.sim_max_iterations, 10000000)
Generic name: MSK_IPAR_SIM_MAX_ITERATIONS
Groups: Simplex optimizer, Termination criteria

iparam.sim_max_num_setbacks¶

Controls how many set-backs are allowed within a simplex optimizer. A set-back is an event where the optimizer moves in the wrong direction. This is impossible in theory but may happen due to numerical problems.

Default: 250
Accepted: [0; +inf]
Example: task.putintparam(iparam.sim_max_num_setbacks, 250)
Generic name: MSK_IPAR_SIM_MAX_NUM_SETBACKS
Groups: Simplex optimizer

iparam.sim_non_singular¶

Controls if the simplex optimizer ensures a non-singular basis, if possible.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.sim_non_singular, onoffkey.on.value)
Generic name: MSK_IPAR_SIM_NON_SINGULAR
Groups: Simplex optimizer

iparam.sim_primal_crash¶

Controls whether crashing is performed in the primal simplex optimizer. In general, if a basis consists of more than (100-this parameter value)% fixed variables, then a crash will be performed.

Default: 90
Accepted: [0; +inf]
Example: task.putintparam(iparam.sim_primal_crash, 90)
Generic name: MSK_IPAR_SIM_PRIMAL_CRASH
Groups: Primal simplex

iparam.sim_primal_phaseone_method¶

An experimental feature.

Default: 0
Accepted: [0; 10]
Example: task.putintparam(iparam.sim_primal_phaseone_method, 0)
Generic name: MSK_IPAR_SIM_PRIMAL_PHASEONE_METHOD
Groups: Simplex optimizer

iparam.sim_primal_restrict_selection¶

The primal simplex optimizer can use a so-called restricted selection/pricing strategy to choose the outgoing variable. Hence, if restricted selection is applied, then the primal simplex optimizer first choose a subset of all the potential incoming variables. Next, for some time it will choose the incoming variable only among the subset. From time to time the subset is redefined. A larger value of this parameter implies that the optimizer will be more aggressive in its restriction strategy, i.e. a value of 0 implies that the restriction strategy is not applied at all.

Default: 50
Accepted: [0; 100]
Example: task.putintparam(iparam.sim_primal_restrict_selection, 50)
Generic name: MSK_IPAR_SIM_PRIMAL_RESTRICT_SELECTION
Groups: Primal simplex

iparam.sim_primal_selection¶

Controls the choice of the incoming variable, known as the selection strategy, in the primal simplex optimizer.

Default: free
Accepted: free, full, ase, devex, se, partial (see simseltype)
Example: task.putintparam(iparam.sim_primal_selection, simseltype.free.value)
Generic name: MSK_IPAR_SIM_PRIMAL_SELECTION
Groups: Primal simplex

iparam.sim_refactor_freq¶

Controls how frequent the basis is refactorized. The value 0 means that the optimizer determines the best point of refactorization. It is strongly recommended NOT to change this parameter.

Default: 0
Accepted: [0; +inf]
Example: task.putintparam(iparam.sim_refactor_freq, 0)
Generic name: MSK_IPAR_SIM_REFACTOR_FREQ
Groups: Simplex optimizer

iparam.sim_reformulation¶

Controls if the simplex optimizers are allowed to reformulate the problem.

Default: off
Accepted: on, off, free, aggressive (see simreform)
Example: task.putintparam(iparam.sim_reformulation, simreform.off.value)
Generic name: MSK_IPAR_SIM_REFORMULATION
Groups: Simplex optimizer

iparam.sim_save_lu¶

Controls if the LU factorization stored should be replaced with the LU factorization corresponding to the initial basis.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.sim_save_lu, onoffkey.off.value)
Generic name: MSK_IPAR_SIM_SAVE_LU
Groups: Simplex optimizer

iparam.sim_scaling¶

Controls how much effort is used in scaling the problem before a simplex optimizer is used.

Default: free
Accepted: free, none (see scalingtype)
Example: task.putintparam(iparam.sim_scaling, scalingtype.free.value)
Generic name: MSK_IPAR_SIM_SCALING
Groups: Simplex optimizer

iparam.sim_scaling_method¶

Controls how the problem is scaled before a simplex optimizer is used.

Default: pow2
Accepted: pow2, free (see scalingmethod)
Example: task.putintparam(iparam.sim_scaling_method, scalingmethod.pow2.value)
Generic name: MSK_IPAR_SIM_SCALING_METHOD
Groups: Simplex optimizer

iparam.sim_seed¶

Sets the random seed used for randomization in the simplex optimizers.

Default: 23456
Accepted: [0; 32749]
Example: task.putintparam(iparam.sim_seed, 23456)
Generic name: MSK_IPAR_SIM_SEED
Groups: Simplex optimizer

iparam.sim_solve_form¶

Controls whether the primal or the dual problem is solved by the primal-/dual-simplex optimizer.

Default: free
Accepted: free, primal, dual (see solveform)
Example: task.putintparam(iparam.sim_solve_form, solveform.free.value)
Generic name: MSK_IPAR_SIM_SOLVE_FORM
Groups: Simplex optimizer

iparam.sim_stability_priority¶

Controls how high priority the numerical stability should be given.

Default: 50
Accepted: [0; 100]
Example: task.putintparam(iparam.sim_stability_priority, 50)
Generic name: MSK_IPAR_SIM_STABILITY_PRIORITY
Groups: Simplex optimizer

iparam.sim_switch_optimizer¶

The simplex optimizer sometimes chooses to solve the dual problem instead of the primal problem. This implies that if you have chosen to use the dual simplex optimizer and the problem is dualized, then it actually makes sense to use the primal simplex optimizer instead. If this parameter is on and the problem is dualized and furthermore the simplex optimizer is chosen to be the primal (dual) one, then it is switched to the dual (primal).

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.sim_switch_optimizer, onoffkey.off.value)
Generic name: MSK_IPAR_SIM_SWITCH_OPTIMIZER
Groups: Simplex optimizer

iparam.sol_filter_keep_basic¶

If turned on, then basic and super basic constraints and variables are written to the solution file independent of the filter setting.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.sol_filter_keep_basic, onoffkey.off.value)
Generic name: MSK_IPAR_SOL_FILTER_KEEP_BASIC
Groups: Solution input/output

iparam.sol_filter_keep_ranged¶

If turned on, then ranged constraints and variables are written to the solution file independent of the filter setting.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.sol_filter_keep_ranged, onoffkey.off.value)
Generic name: MSK_IPAR_SOL_FILTER_KEEP_RANGED
Groups: Solution input/output

iparam.sol_read_name_width¶

When a solution is read by MOSEK and some constraint, variable or cone names contain blanks, then a maximum name width much be specified. A negative value implies that no name contain blanks.

Default: -1
Accepted: [-inf; +inf]
Example: task.putintparam(iparam.sol_read_name_width, -1)
Generic name: MSK_IPAR_SOL_READ_NAME_WIDTH
Groups: Data input/output, Solution input/output

iparam.sol_read_width¶

Controls the maximal acceptable width of line in the solutions when read by MOSEK.

Default: 1024
Accepted: [80; +inf]
Example: task.putintparam(iparam.sol_read_width, 1024)
Generic name: MSK_IPAR_SOL_READ_WIDTH
Groups: Data input/output, Solution input/output

iparam.solution_callback¶

Indicates whether solution callbacks will be performed during the optimization.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.solution_callback, onoffkey.off.value)
Generic name: MSK_IPAR_SOLUTION_CALLBACK
Groups: Progress callback, Overall solver

iparam.timing_level¶

Controls the amount of timing performed inside MOSEK.

Default: 1
Accepted: [0; +inf]
Example: task.putintparam(iparam.timing_level, 1)
Generic name: MSK_IPAR_TIMING_LEVEL
Groups: Overall system

iparam.write_bas_constraints¶

Controls whether the constraint section is written to the basic solution file.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.write_bas_constraints, onoffkey.on.value)
Generic name: MSK_IPAR_WRITE_BAS_CONSTRAINTS
Groups: Data input/output, Solution input/output

iparam.write_bas_head¶

Controls whether the header section is written to the basic solution file.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.write_bas_head, onoffkey.on.value)
Generic name: MSK_IPAR_WRITE_BAS_HEAD
Groups: Data input/output, Solution input/output

iparam.write_bas_variables¶

Controls whether the variables section is written to the basic solution file.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.write_bas_variables, onoffkey.on.value)
Generic name: MSK_IPAR_WRITE_BAS_VARIABLES
Groups: Data input/output, Solution input/output

iparam.write_compression¶

Controls whether the data file is compressed while it is written. 0 means no compression while higher values mean more compression.

Default: 9
Accepted: [0; +inf]
Example: task.putintparam(iparam.write_compression, 9)
Generic name: MSK_IPAR_WRITE_COMPRESSION
Groups: Data input/output

iparam.write_data_param¶

If this option is turned on the parameter settings are written to the data file as parameters.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.write_data_param, onoffkey.off.value)
Generic name: MSK_IPAR_WRITE_DATA_PARAM
Groups: Data input/output

iparam.write_free_con¶

Controls whether the free constraints are written to the data file.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.write_free_con, onoffkey.on.value)
Generic name: MSK_IPAR_WRITE_FREE_CON
Groups: Data input/output

iparam.write_generic_names¶

Controls whether generic names should be used instead of user-defined names when writing to the data file.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.write_generic_names, onoffkey.off.value)
Generic name: MSK_IPAR_WRITE_GENERIC_NAMES
Groups: Data input/output

iparam.write_generic_names_io¶

Index origin used in generic names.

Default: 1
Accepted: [0; +inf]
Example: task.putintparam(iparam.write_generic_names_io, 1)
Generic name: MSK_IPAR_WRITE_GENERIC_NAMES_IO
Groups: Data input/output

iparam.write_ignore_incompatible_items¶

Controls if the writer ignores incompatible problem items when writing files.

Default

off

Accepted

on: Ignore items that cannot be written to the current output file format.
off: Produce an error if the problem contains items that cannot the written to the current output file format.

Example

task.putintparam(iparam.write_ignore_incompatible_items, onoffkey.off.value)

Generic name

MSK_IPAR_WRITE_IGNORE_INCOMPATIBLE_ITEMS

Groups

Data input/output

iparam.write_int_constraints¶

Controls whether the constraint section is written to the integer solution file.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.write_int_constraints, onoffkey.on.value)
Generic name: MSK_IPAR_WRITE_INT_CONSTRAINTS
Groups: Data input/output, Solution input/output

iparam.write_int_head¶

Controls whether the header section is written to the integer solution file.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.write_int_head, onoffkey.on.value)
Generic name: MSK_IPAR_WRITE_INT_HEAD
Groups: Data input/output, Solution input/output

iparam.write_int_variables¶

Controls whether the variables section is written to the integer solution file.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.write_int_variables, onoffkey.on.value)
Generic name: MSK_IPAR_WRITE_INT_VARIABLES
Groups: Data input/output, Solution input/output

iparam.write_json_indentation¶

When set, the JSON task and solution files are written with indentation for better readability.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.write_json_indentation, onoffkey.off.value)
Generic name: MSK_IPAR_WRITE_JSON_INDENTATION
Groups: Data input/output

iparam.write_lp_full_obj¶

Write all variables, including the ones with 0-coefficients, in the objective.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.write_lp_full_obj, onoffkey.on.value)
Generic name: MSK_IPAR_WRITE_LP_FULL_OBJ
Groups: Data input/output

iparam.write_lp_line_width¶

Maximum width of line in an LP file written by MOSEK.

Default: 80
Accepted: [40; +inf]
Example: task.putintparam(iparam.write_lp_line_width, 80)
Generic name: MSK_IPAR_WRITE_LP_LINE_WIDTH
Groups: Data input/output

iparam.write_mps_format¶

Controls in which format the MPS is written.

Default: free
Accepted: strict, relaxed, free, cplex (see mpsformat)
Example: task.putintparam(iparam.write_mps_format, mpsformat.free.value)
Generic name: MSK_IPAR_WRITE_MPS_FORMAT
Groups: Data input/output

iparam.write_mps_int¶

Controls if marker records are written to the MPS file to indicate whether variables are integer restricted.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.write_mps_int, onoffkey.on.value)
Generic name: MSK_IPAR_WRITE_MPS_INT
Groups: Data input/output

iparam.write_sol_barvariables¶

Controls whether the symmetric matrix variables section is written to the solution file.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.write_sol_barvariables, onoffkey.on.value)
Generic name: MSK_IPAR_WRITE_SOL_BARVARIABLES
Groups: Data input/output, Solution input/output

iparam.write_sol_constraints¶

Controls whether the constraint section is written to the solution file.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.write_sol_constraints, onoffkey.on.value)
Generic name: MSK_IPAR_WRITE_SOL_CONSTRAINTS
Groups: Data input/output, Solution input/output

iparam.write_sol_head¶

Controls whether the header section is written to the solution file.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.write_sol_head, onoffkey.on.value)
Generic name: MSK_IPAR_WRITE_SOL_HEAD
Groups: Data input/output, Solution input/output

iparam.write_sol_ignore_invalid_names¶

Even if the names are invalid MPS names, then they are employed when writing the solution file.

Default: off
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.write_sol_ignore_invalid_names, onoffkey.off.value)
Generic name: MSK_IPAR_WRITE_SOL_IGNORE_INVALID_NAMES
Groups: Data input/output, Solution input/output

iparam.write_sol_variables¶

Controls whether the variables section is written to the solution file.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.write_sol_variables, onoffkey.on.value)
Generic name: MSK_IPAR_WRITE_SOL_VARIABLES
Groups: Data input/output, Solution input/output

iparam.write_task_inc_sol¶

Controls whether the solutions are stored in the task file too.

Default: on
Accepted: on, off (see onoffkey)
Example: task.putintparam(iparam.write_task_inc_sol, onoffkey.on.value)
Generic name: MSK_IPAR_WRITE_TASK_INC_SOL
Groups: Data input/output

iparam.write_xml_mode¶

Controls if linear coefficients should be written by row or column when writing in the XML file format.

Default: row
Accepted: row, col (see xmlwriteroutputtype)
Example: task.putintparam(iparam.write_xml_mode, xmlwriteroutputtype.row.value)
Generic name: MSK_IPAR_WRITE_XML_MODE
Groups: Data input/output

15.7.3 String parameters¶

sparam¶: The enumeration type containing all string parameters.

sparam.bas_sol_file_name¶

Name of the bas solution file.

Accepted: Any valid file name.
Example: task.putstrparam(sparam.bas_sol_file_name, "somevalue")
Generic name: MSK_SPAR_BAS_SOL_FILE_NAME
Groups: Data input/output, Solution input/output

sparam.data_file_name¶

Data are read and written to this file.

Accepted: Any valid file name.
Example: task.putstrparam(sparam.data_file_name, "somevalue")
Generic name: MSK_SPAR_DATA_FILE_NAME
Groups: Data input/output

sparam.debug_file_name¶

MOSEK debug file.

Accepted: Any valid file name.
Example: task.putstrparam(sparam.debug_file_name, "somevalue")
Generic name: MSK_SPAR_DEBUG_FILE_NAME
Groups: Data input/output

sparam.int_sol_file_name¶

Name of the int solution file.

Accepted: Any valid file name.
Example: task.putstrparam(sparam.int_sol_file_name, "somevalue")
Generic name: MSK_SPAR_INT_SOL_FILE_NAME
Groups: Data input/output, Solution input/output

sparam.itr_sol_file_name¶

Name of the itr solution file.

Accepted: Any valid file name.
Example: task.putstrparam(sparam.itr_sol_file_name, "somevalue")
Generic name: MSK_SPAR_ITR_SOL_FILE_NAME
Groups: Data input/output, Solution input/output

sparam.mio_debug_string¶

For internal debugging purposes.

Accepted: Any valid string.
Example: task.putstrparam(sparam.mio_debug_string, "somevalue")
Generic name: MSK_SPAR_MIO_DEBUG_STRING
Groups: Data input/output

sparam.param_comment_sign¶

Only the first character in this string is used. It is considered as a start of comment sign in the MOSEK parameter file. Spaces are ignored in the string.

Default

%%

Accepted

Any valid string.

Example

task.putstrparam(sparam.param_comment_sign, "%%")

Generic name

MSK_SPAR_PARAM_COMMENT_SIGN

Groups

Data input/output

sparam.param_read_file_name¶

Modifications to the parameter database is read from this file.

Accepted: Any valid file name.
Example: task.putstrparam(sparam.param_read_file_name, "somevalue")
Generic name: MSK_SPAR_PARAM_READ_FILE_NAME
Groups: Data input/output

sparam.param_write_file_name¶

The parameter database is written to this file.

Accepted: Any valid file name.
Example: task.putstrparam(sparam.param_write_file_name, "somevalue")
Generic name: MSK_SPAR_PARAM_WRITE_FILE_NAME
Groups: Data input/output

sparam.read_mps_bou_name¶

Name of the BOUNDS vector used. An empty name means that the first BOUNDS vector is used.

Accepted: Any valid MPS name.
Example: task.putstrparam(sparam.read_mps_bou_name, "somevalue")
Generic name: MSK_SPAR_READ_MPS_BOU_NAME
Groups: Data input/output

sparam.read_mps_obj_name¶

Name of the free constraint used as objective function. An empty name means that the first constraint is used as objective function.

Accepted: Any valid MPS name.
Example: task.putstrparam(sparam.read_mps_obj_name, "somevalue")
Generic name: MSK_SPAR_READ_MPS_OBJ_NAME
Groups: Data input/output

sparam.read_mps_ran_name¶

Name of the RANGE vector used. An empty name means that the first RANGE vector is used.

Accepted: Any valid MPS name.
Example: task.putstrparam(sparam.read_mps_ran_name, "somevalue")
Generic name: MSK_SPAR_READ_MPS_RAN_NAME
Groups: Data input/output

sparam.read_mps_rhs_name¶

Name of the RHS used. An empty name means that the first RHS vector is used.

Accepted: Any valid MPS name.
Example: task.putstrparam(sparam.read_mps_rhs_name, "somevalue")
Generic name: MSK_SPAR_READ_MPS_RHS_NAME
Groups: Data input/output

sparam.remote_optserver_host¶

URL of the remote optimization server in the format (http|https)://server:port. If set, all subsequent calls to any MOSEK function that involves synchronous optimization will be sent to the specified OptServer instead of being executed locally. Passing empty string deactivates this redirection.

Accepted: Any valid URL.
Example: task.putstrparam(sparam.remote_optserver_host, "somevalue")
Generic name: MSK_SPAR_REMOTE_OPTSERVER_HOST
Groups: Overall system

sparam.remote_tls_cert¶

List of known server certificates in PEM format.

Accepted: PEM files separated by new-lines.
Example: task.putstrparam(sparam.remote_tls_cert, "somevalue")
Generic name: MSK_SPAR_REMOTE_TLS_CERT
Groups: Overall system

sparam.remote_tls_cert_path¶

Path to known server certificates in PEM format.

Accepted: Any valid path.
Example: task.putstrparam(sparam.remote_tls_cert_path, "somevalue")
Generic name: MSK_SPAR_REMOTE_TLS_CERT_PATH
Groups: Overall system

sparam.sensitivity_file_name¶

If defined Task.sensitivityreport reads this file as a sensitivity analysis data file specifying the type of analysis to be done.

Accepted: Any valid string.
Example: task.putstrparam(sparam.sensitivity_file_name, "somevalue")
Generic name: MSK_SPAR_SENSITIVITY_FILE_NAME
Groups: Data input/output

sparam.sensitivity_res_file_name¶

If this is a nonempty string, then Task.sensitivityreport writes results to this file.

Accepted: Any valid string.
Example: task.putstrparam(sparam.sensitivity_res_file_name, "somevalue")
Generic name: MSK_SPAR_SENSITIVITY_RES_FILE_NAME
Groups: Data input/output

sparam.sol_filter_xc_low¶

A filter used to determine which constraints should be listed in the solution file. A value of \(0.5\) means that all constraints having xc[i]>0.5 should be listed, whereas +0.5 means that all constraints having xc[i]>=blc[i]+0.5 should be listed. An empty filter means that no filter is applied.

Accepted: Any valid filter.
Example: task.putstrparam(sparam.sol_filter_xc_low, "somevalue")
Generic name: MSK_SPAR_SOL_FILTER_XC_LOW
Groups: Data input/output, Solution input/output

sparam.sol_filter_xc_upr¶

A filter used to determine which constraints should be listed in the solution file. A value of 0.5 means that all constraints having xc[i]<0.5 should be listed, whereas -0.5 means all constraints having xc[i]<=buc[i]-0.5 should be listed. An empty filter means that no filter is applied.

Accepted: Any valid filter.
Example: task.putstrparam(sparam.sol_filter_xc_upr, "somevalue")
Generic name: MSK_SPAR_SOL_FILTER_XC_UPR
Groups: Data input/output, Solution input/output

sparam.sol_filter_xx_low¶

A filter used to determine which variables should be listed in the solution file. A value of “0.5” means that all constraints having xx[j]>=0.5 should be listed, whereas “+0.5” means that all constraints having xx[j]>=blx[j]+0.5 should be listed. An empty filter means no filter is applied.

Accepted: Any valid filter.
Example: task.putstrparam(sparam.sol_filter_xx_low, "somevalue")
Generic name: MSK_SPAR_SOL_FILTER_XX_LOW
Groups: Data input/output, Solution input/output

sparam.sol_filter_xx_upr¶

A filter used to determine which variables should be listed in the solution file. A value of “0.5” means that all constraints having xx[j]<0.5 should be printed, whereas “-0.5” means all constraints having xx[j]<=bux[j]-0.5 should be listed. An empty filter means no filter is applied.

Accepted: Any valid file name.
Example: task.putstrparam(sparam.sol_filter_xx_upr, "somevalue")
Generic name: MSK_SPAR_SOL_FILTER_XX_UPR
Groups: Data input/output, Solution input/output

sparam.stat_key¶

Key used when writing the summary file.

Accepted: Any valid string.
Example: task.putstrparam(sparam.stat_key, "somevalue")
Generic name: MSK_SPAR_STAT_KEY
Groups: Data input/output

sparam.stat_name¶

Name used when writing the statistics file.

Accepted: Any valid XML string.
Example: task.putstrparam(sparam.stat_name, "somevalue")
Generic name: MSK_SPAR_STAT_NAME
Groups: Data input/output

sparam.write_lp_gen_var_name¶

Sometimes when an LP file is written additional variables must be inserted. They will have the prefix denoted by this parameter.

Default: xmskgen
Accepted: Any valid string.
Example: task.putstrparam(sparam.write_lp_gen_var_name, "xmskgen")
Generic name: MSK_SPAR_WRITE_LP_GEN_VAR_NAME
Groups: Data input/output

15.7 Parameters (alphabetical list sorted by type)¶

15.7.1 Double parameters¶

15.7.2 Integer parameters¶

15.7.3 String parameters¶

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