16.9 Enumerations¶

language
¶ Language selection constants

language.eng
¶ English language selection

language.dan
¶ Danish language selection


accmode
¶ Constraint or variable access modes. All functions using this enum are deprecated. Use separate functions for rows/columns instead.

accmode.var
¶ Access data by columns (variable oriented)

accmode.con
¶ Access data by rows (constraint oriented)


basindtype
¶ Basis identification

basindtype.never
¶ Never do basis identification.

basindtype.always
¶ Basis identification is always performed even if the interiorpoint optimizer terminates abnormally.

basindtype.no_error
¶ Basis identification is performed if the interiorpoint optimizer terminates without an error.

basindtype.if_feasible
¶ Basis identification is not performed if the interiorpoint optimizer terminates with a problem status saying that the problem is primal or dual infeasible.

basindtype.reservered
¶ Not currently in use.


boundkey
¶ Bound keys

boundkey.lo
¶ The constraint or variable has a finite lower bound and an infinite upper bound.

boundkey.up
¶ The constraint or variable has an infinite lower bound and an finite upper bound.

boundkey.fx
¶ The constraint or variable is fixed.

boundkey.fr
¶ The constraint or variable is free.

boundkey.ra
¶ The constraint or variable is ranged.


mark
¶ Mark

mark.lo
¶ The lower bound is selected for sensitivity analysis.

mark.up
¶ The upper bound is selected for sensitivity analysis.


simdegen
¶ Degeneracy strategies

simdegen.none
¶ The simplex optimizer should use no degeneration strategy.

simdegen.free
¶ The simplex optimizer chooses the degeneration strategy.

simdegen.aggressive
¶ The simplex optimizer should use an aggressive degeneration strategy.

simdegen.moderate
¶ The simplex optimizer should use a moderate degeneration strategy.

simdegen.minimum
¶ The simplex optimizer should use a minimum degeneration strategy.


transpose
¶ Transposed matrix.

transpose.no
¶ No transpose is applied.

transpose.yes
¶ A transpose is applied.


simreform
¶ Problem reformulation.

simreform.on
¶ Allow the simplex optimizer to reformulate the problem.

simreform.off
¶ Disallow the simplex optimizer to reformulate the problem.

simreform.free
¶ The simplex optimizer can choose freely.

simreform.aggressive
¶ The simplex optimizer should use an aggressive reformulation strategy.


simdupvec
¶ Exploit duplicate columns.

simdupvec.on
¶ Allow the simplex optimizer to exploit duplicated columns.

simdupvec.off
¶ Disallow the simplex optimizer to exploit duplicated columns.

simdupvec.free
¶ The simplex optimizer can choose freely.


simhotstart
¶ Hotstart type employed by the simplex optimizer

simhotstart.none
¶ The simplex optimizer performs a coldstart.

simhotstart.free
¶ The simplex optimize chooses the hotstart type.

simhotstart.status_keys
¶ Only the status keys of the constraints and variables are used to choose the type of hotstart.


intpnthotstart
¶ Hotstart type employed by the interiorpoint optimizers.

intpnthotstart.none
¶ The interiorpoint optimizer performs a coldstart.

intpnthotstart.primal
¶ The interiorpoint optimizer exploits the primal solution only.

intpnthotstart.dual
¶ The interiorpoint optimizer exploits the dual solution only.

intpnthotstart.primal_dual
¶ The interiorpoint optimizer exploits both the primal and dual solution.


callbackcode
¶ Progress callback codes

callbackcode.begin_bi
¶ The basis identification procedure has been started.

callbackcode.begin_conic
¶ The callback function is called when the conic optimizer is started.

callbackcode.begin_dual_bi
¶ The callback function is called from within the basis identification procedure when the dual phase is started.

callbackcode.begin_dual_sensitivity
¶ Dual sensitivity analysis is started.

callbackcode.begin_dual_setup_bi
¶ The callback function is called when the dual BI phase is started.

callbackcode.begin_dual_simplex
¶ The callback function is called when the dual simplex optimizer started.

callbackcode.begin_dual_simplex_bi
¶ The callback function is called from within the basis identification procedure when the dual simplex cleanup phase is started.

callbackcode.begin_full_convexity_check
¶ Begin full convexity check.

callbackcode.begin_infeas_ana
¶ The callback function is called when the infeasibility analyzer is started.

callbackcode.begin_intpnt
¶ The callback function is called when the interiorpoint optimizer is started.

callbackcode.begin_license_wait
¶ Begin waiting for license.

callbackcode.begin_mio
¶ The callback function is called when the mixedinteger optimizer is started.

callbackcode.begin_optimizer
¶ The callback function is called when the optimizer is started.

callbackcode.begin_presolve
¶ The callback function is called when the presolve is started.

callbackcode.begin_primal_bi
¶ The callback function is called from within the basis identification procedure when the primal phase is started.

callbackcode.begin_primal_repair
¶ Begin primal feasibility repair.

callbackcode.begin_primal_sensitivity
¶ Primal sensitivity analysis is started.

callbackcode.begin_primal_setup_bi
¶ The callback function is called when the primal BI setup is started.

callbackcode.begin_primal_simplex
¶ The callback function is called when the primal simplex optimizer is started.

callbackcode.begin_primal_simplex_bi
¶ The callback function is called from within the basis identification procedure when the primal simplex cleanup phase is started.

callbackcode.begin_qcqo_reformulate
¶ Begin QCQO reformulation.

callbackcode.begin_read
¶ MOSEK has started reading a problem file.

callbackcode.begin_root_cutgen
¶ The callback function is called when root cut generation is started.

callbackcode.begin_simplex
¶ The callback function is called when the simplex optimizer is started.

callbackcode.begin_simplex_bi
¶ The callback function is called from within the basis identification procedure when the simplex cleanup phase is started.

callbackcode.begin_to_conic
¶ Begin conic reformulation.

callbackcode.begin_write
¶ MOSEK has started writing a problem file.

callbackcode.conic
¶ The callback function is called from within the conic optimizer after the information database has been updated.

callbackcode.dual_simplex
¶ The callback function is called from within the dual simplex optimizer.

callbackcode.end_bi
¶ The callback function is called when the basis identification procedure is terminated.

callbackcode.end_conic
¶ The callback function is called when the conic optimizer is terminated.

callbackcode.end_dual_bi
¶ The callback function is called from within the basis identification procedure when the dual phase is terminated.

callbackcode.end_dual_sensitivity
¶ Dual sensitivity analysis is terminated.

callbackcode.end_dual_setup_bi
¶ The callback function is called when the dual BI phase is terminated.

callbackcode.end_dual_simplex
¶ The callback function is called when the dual simplex optimizer is terminated.

callbackcode.end_dual_simplex_bi
¶ The callback function is called from within the basis identification procedure when the dual cleanup phase is terminated.

callbackcode.end_full_convexity_check
¶ End full convexity check.

callbackcode.end_infeas_ana
¶ The callback function is called when the infeasibility analyzer is terminated.

callbackcode.end_intpnt
¶ The callback function is called when the interiorpoint optimizer is terminated.

callbackcode.end_license_wait
¶ End waiting for license.

callbackcode.end_mio
¶ The callback function is called when the mixedinteger optimizer is terminated.

callbackcode.end_optimizer
¶ The callback function is called when the optimizer is terminated.

callbackcode.end_presolve
¶ The callback function is called when the presolve is completed.

callbackcode.end_primal_bi
¶ The callback function is called from within the basis identification procedure when the primal phase is terminated.

callbackcode.end_primal_repair
¶ End primal feasibility repair.

callbackcode.end_primal_sensitivity
¶ Primal sensitivity analysis is terminated.

callbackcode.end_primal_setup_bi
¶ The callback function is called when the primal BI setup is terminated.

callbackcode.end_primal_simplex
¶ The callback function is called when the primal simplex optimizer is terminated.

callbackcode.end_primal_simplex_bi
¶ The callback function is called from within the basis identification procedure when the primal cleanup phase is terminated.

callbackcode.end_qcqo_reformulate
¶ End QCQO reformulation.

callbackcode.end_read
¶ MOSEK has finished reading a problem file.

callbackcode.end_root_cutgen
¶ The callback function is called when root cut generation is is terminated.

callbackcode.end_simplex
¶ The callback function is called when the simplex optimizer is terminated.

callbackcode.end_simplex_bi
¶ The callback function is called from within the basis identification procedure when the simplex cleanup phase is terminated.

callbackcode.end_to_conic
¶ End conic reformulation.

callbackcode.end_write
¶ MOSEK has finished writing a problem file.

callbackcode.im_bi
¶ The callback function is called from within the basis identification procedure at an intermediate point.

callbackcode.im_conic
¶ The callback function is called at an intermediate stage within the conic optimizer where the information database has not been updated.

callbackcode.im_dual_bi
¶ The callback function is called from within the basis identification procedure at an intermediate point in the dual phase.

callbackcode.im_dual_sensivity
¶ The callback function is called at an intermediate stage of the dual sensitivity analysis.

callbackcode.im_dual_simplex
¶ The callback function is called at an intermediate point in the dual simplex optimizer.

callbackcode.im_full_convexity_check
¶ The callback function is called at an intermediate stage of the full convexity check.

callbackcode.im_intpnt
¶ The callback function is called at an intermediate stage within the interiorpoint optimizer where the information database has not been updated.

callbackcode.im_license_wait
¶ MOSEK is waiting for a license.

callbackcode.im_lu
¶ The callback function is called from within the LU factorization procedure at an intermediate point.

callbackcode.im_mio
¶ The callback function is called at an intermediate point in the mixedinteger optimizer.

callbackcode.im_mio_dual_simplex
¶ The callback function is called at an intermediate point in the mixedinteger optimizer while running the dual simplex optimizer.

callbackcode.im_mio_intpnt
¶ The callback function is called at an intermediate point in the mixedinteger optimizer while running the interiorpoint optimizer.

callbackcode.im_mio_primal_simplex
¶ The callback function is called at an intermediate point in the mixedinteger optimizer while running the primal simplex optimizer.

callbackcode.im_order
¶ The callback function is called from within the matrix ordering procedure at an intermediate point.

callbackcode.im_presolve
¶ The callback function is called from within the presolve procedure at an intermediate stage.

callbackcode.im_primal_bi
¶ The callback function is called from within the basis identification procedure at an intermediate point in the primal phase.

callbackcode.im_primal_sensivity
¶ The callback function is called at an intermediate stage of the primal sensitivity analysis.

callbackcode.im_primal_simplex
¶ The callback function is called at an intermediate point in the primal simplex optimizer.

callbackcode.im_qo_reformulate
¶ The callback function is called at an intermediate stage of the conic quadratic reformulation.

callbackcode.im_read
¶ Intermediate stage in reading.

callbackcode.im_root_cutgen
¶ The callback is called from within root cut generation at an intermediate stage.

callbackcode.im_simplex
¶ The callback function is called from within the simplex optimizer at an intermediate point.

callbackcode.im_simplex_bi
¶ The callback function is called from within the basis identification procedure at an intermediate point in the simplex cleanup phase. The frequency of the callbacks is controlled by the
iparam.log_sim_freq
parameter.

callbackcode.intpnt
¶ The callback function is called from within the interiorpoint optimizer after the information database has been updated.

callbackcode.new_int_mio
¶ The callback function is called after a new integer solution has been located by the mixedinteger optimizer.

callbackcode.primal_simplex
¶ The callback function is called from within the primal simplex optimizer.

callbackcode.read_opf
¶ The callback function is called from the OPF reader.

callbackcode.read_opf_section
¶ A chunk of \(Q\) nonzeros has been read from a problem file.

callbackcode.solving_remote
¶ The callback function is called while the task is being solved on a remote server.

callbackcode.update_dual_bi
¶ The callback function is called from within the basis identification procedure at an intermediate point in the dual phase.

callbackcode.update_dual_simplex
¶ The callback function is called in the dual simplex optimizer.

callbackcode.update_dual_simplex_bi
¶ The callback function is called from within the basis identification procedure at an intermediate point in the dual simplex cleanup phase. The frequency of the callbacks is controlled by the
iparam.log_sim_freq
parameter.

callbackcode.update_presolve
¶ The callback function is called from within the presolve procedure.

callbackcode.update_primal_bi
¶ The callback function is called from within the basis identification procedure at an intermediate point in the primal phase.

callbackcode.update_primal_simplex
¶ The callback function is called in the primal simplex optimizer.

callbackcode.update_primal_simplex_bi
¶ The callback function is called from within the basis identification procedure at an intermediate point in the primal simplex cleanup phase. The frequency of the callbacks is controlled by the
iparam.log_sim_freq
parameter.

callbackcode.write_opf
¶ The callback function is called from the OPF writer.


checkconvexitytype
¶ Types of convexity checks.

checkconvexitytype.none
¶ No convexity check.

checkconvexitytype.simple
¶ Perform simple and fast convexity check.

checkconvexitytype.full
¶ Perform a full convexity check.


compresstype
¶ Compression types

compresstype.none
¶ No compression is used.

compresstype.free
¶ The type of compression used is chosen automatically.

compresstype.gzip
¶ The type of compression used is gzip compatible.


conetype
¶ Cone types

conetype.quad
¶ The cone is a quadratic cone.

conetype.rquad
¶ The cone is a rotated quadratic cone.


nametype
¶ Name types

nametype.gen
¶ General names. However, no duplicate and blank names are allowed.

nametype.mps
¶ MPS type names.

nametype.lp
¶ LP type names.


dataformat
¶ Data format types

dataformat.extension
¶ The file extension is used to determine the data file format.

dataformat.mps
¶ The data file is MPS formatted.

dataformat.lp
¶ The data file is LP formatted.

dataformat.op
¶ The data file is an optimization problem formatted file.

dataformat.xml
¶ The data file is an XML formatted file.

dataformat.free_mps
¶ The data a free MPS formatted file.

dataformat.task
¶ Generic task dump file.

dataformat.cb
¶ Conic benchmark format,

dataformat.json_task
¶ JSON based task format.


dinfitem
¶ Double information items

dinfitem.bi_clean_dual_time
¶ Time spent within the dual cleanup optimizer of the basis identification procedure since its invocation.

dinfitem.bi_clean_primal_time
¶ Time spent within the primal cleanup optimizer of the basis identification procedure since its invocation.

dinfitem.bi_clean_time
¶ Time spent within the cleanup phase of the basis identification procedure since its invocation.

dinfitem.bi_dual_time
¶ Time spent within the dual phase basis identification procedure since its invocation.

dinfitem.bi_primal_time
¶ Time spent within the primal phase of the basis identification procedure since its invocation.

dinfitem.bi_time
¶ Time spent within the basis identification procedure since its invocation.

dinfitem.intpnt_dual_feas
¶ Dual feasibility measure reported by the interiorpoint optimizer. (For the interiorpoint optimizer this measure is not directly related to the original problem because a homogeneous model is employed.)

dinfitem.intpnt_dual_obj
¶ Dual objective value reported by the interiorpoint optimizer.

dinfitem.intpnt_factor_num_flops
¶ An estimate of the number of flops used in the factorization.

dinfitem.intpnt_opt_status
¶ A measure of optimality of the solution. It should converge to \(+1\) if the problem has a primaldual optimal solution, and converge to \(1\) if the problem is (strictly) primal or dual infeasible. If the measure converges to another constant, or fails to settle, the problem is usually illposed.

dinfitem.intpnt_order_time
¶ Order time (in seconds).

dinfitem.intpnt_primal_feas
¶ Primal feasibility measure reported by the interiorpoint optimizer. (For the interiorpoint optimizer this measure is not directly related to the original problem because a homogeneous model is employed).

dinfitem.intpnt_primal_obj
¶ Primal objective value reported by the interiorpoint optimizer.

dinfitem.intpnt_time
¶ Time spent within the interiorpoint optimizer since its invocation.

dinfitem.mio_clique_separation_time
¶ Seperation time for clique cuts.

dinfitem.mio_cmir_separation_time
¶ Seperation time for CMIR cuts.

dinfitem.mio_construct_solution_obj
¶ If MOSEK has successfully constructed an integer feasible solution, then this item contains the optimal objective value corresponding to the feasible solution.

dinfitem.mio_dual_bound_after_presolve
¶ Value of the dual bound after presolve but before cut generation.

dinfitem.mio_gmi_separation_time
¶ Seperation time for GMI cuts.

dinfitem.mio_heuristic_time
¶ Total time spent in the optimizer.

dinfitem.mio_implied_bound_time
¶ Seperation time for implied bound cuts.

dinfitem.mio_knapsack_cover_separation_time
¶ Seperation time for knapsack cover.

dinfitem.mio_obj_abs_gap
¶ Given the mixedinteger optimizer has computed a feasible solution and a bound on the optimal objective value, then this item contains the absolute gap defined by
\[\mbox{(objective value of feasible solution)}\mbox{(objective bound)}.\]Otherwise it has the value 1.0.

dinfitem.mio_obj_bound
¶ The best known bound on the objective function. This value is undefined until at least one relaxation has been solved: To see if this is the case check that
iinfitem.mio_num_relax
is strictly positive.

dinfitem.mio_obj_int
¶ The primal objective value corresponding to the best integer feasible solution. Please note that at least one integer feasible solution must have been located i.e. check
iinfitem.mio_num_int_solutions
.

dinfitem.mio_obj_rel_gap
¶ Given that the mixedinteger optimizer has computed a feasible solution and a bound on the optimal objective value, then this item contains the relative gap defined by
\[\frac{ \mbox{(objective value of feasible solution)}\mbox{(objective bound)}  }{\max(\delta,\mbox{(objective value of feasible solution)})}.\]where \(\delta\) is given by the parameter
dparam.mio_rel_gap_const
. Otherwise it has the value \(1.0\).

dinfitem.mio_optimizer_time
¶ Total time spent in the optimizer.

dinfitem.mio_probing_time
¶ Total time for probing.

dinfitem.mio_root_cutgen_time
¶ Total time for cut generation.

dinfitem.mio_root_optimizer_time
¶ Time spent in the optimizer while solving the root relaxation.

dinfitem.mio_root_presolve_time
¶ Time spent in while presolving the root relaxation.

dinfitem.mio_time
¶ Time spent in the mixedinteger optimizer.

dinfitem.mio_user_obj_cut
¶ If the objective cut is used, then this information item has the value of the cut.

dinfitem.optimizer_time
¶ Total time spent in the optimizer since it was invoked.

dinfitem.presolve_eli_time
¶ Total time spent in the eliminator since the presolve was invoked.

dinfitem.presolve_lindep_time
¶ Total time spent in the linear dependency checker since the presolve was invoked.

dinfitem.presolve_time
¶ Total time (in seconds) spent in the presolve since it was invoked.

dinfitem.primal_repair_penalty_obj
¶ The optimal objective value of the penalty function.

dinfitem.qcqo_reformulate_max_perturbation
¶ Maximum absolute diagonal perturbation occuring during the QCQO reformulation.

dinfitem.qcqo_reformulate_time
¶ Time spent with conic quadratic reformulation.

dinfitem.qcqo_reformulate_worst_cholesky_column_scaling
¶ Worst Cholesky column scaling.

dinfitem.qcqo_reformulate_worst_cholesky_diag_scaling
¶ Worst Cholesky diagonal scaling.

dinfitem.rd_time
¶ Time spent reading the data file.

dinfitem.sim_dual_time
¶ Time spent in the dual simplex optimizer since invoking it.

dinfitem.sim_feas
¶ Feasibility measure reported by the simplex optimizer.

dinfitem.sim_obj
¶ Objective value reported by the simplex optimizer.

dinfitem.sim_primal_time
¶ Time spent in the primal simplex optimizer since invoking it.

dinfitem.sim_time
¶ Time spent in the simplex optimizer since invoking it.

dinfitem.sol_bas_dual_obj
¶ Dual objective value of the basic solution.

dinfitem.sol_bas_dviolcon
¶ Maximal dual bound violation for \(x^c\) in the basic solution.

dinfitem.sol_bas_dviolvar
¶ Maximal dual bound violation for \(x^x\) in the basic solution.

dinfitem.sol_bas_nrm_barx
¶ Infinity norm of \(\barX\) in the basic solution.

dinfitem.sol_bas_nrm_slc
¶ Infinity norm of \(s_l^c\) in the basic solution.

dinfitem.sol_bas_nrm_slx
¶ Infinity norm of \(s_l^x\) in the basic solution.

dinfitem.sol_bas_nrm_suc
¶ Infinity norm of \(s_u^c\) in the basic solution.

dinfitem.sol_bas_nrm_sux
¶ Infinity norm of \(s_u^X\) in the basic solution.

dinfitem.sol_bas_nrm_xc
¶ Infinity norm of \(x^c\) in the basic solution.

dinfitem.sol_bas_nrm_xx
¶ Infinity norm of \(x^x\) in the basic solution.

dinfitem.sol_bas_nrm_y
¶ Infinity norm of \(y\) in the basic solution.

dinfitem.sol_bas_primal_obj
¶ Primal objective value of the basic solution.

dinfitem.sol_bas_pviolcon
¶ Maximal primal bound violation for \(x^c\) in the basic solution.

dinfitem.sol_bas_pviolvar
¶ Maximal primal bound violation for \(x^x\) in the basic solution.

dinfitem.sol_itg_nrm_barx
¶ Infinity norm of \(\barX\) in the integer solution.

dinfitem.sol_itg_nrm_xc
¶ Infinity norm of \(x^c\) in the integer solution.

dinfitem.sol_itg_nrm_xx
¶ Infinity norm of \(x^x\) in the integer solution.

dinfitem.sol_itg_primal_obj
¶ Primal objective value of the integer solution.

dinfitem.sol_itg_pviolbarvar
¶ Maximal primal bound violation for \(\barX\) in the integer solution.

dinfitem.sol_itg_pviolcon
¶ Maximal primal bound violation for \(x^c\) in the integer solution.

dinfitem.sol_itg_pviolcones
¶ Maximal primal violation for primal conic constraints in the integer solution.

dinfitem.sol_itg_pviolitg
¶ Maximal violation for the integer constraints in the integer solution.

dinfitem.sol_itg_pviolvar
¶ Maximal primal bound violation for \(x^x\) in the integer solution.

dinfitem.sol_itr_dual_obj
¶ Dual objective value of the interiorpoint solution.

dinfitem.sol_itr_dviolbarvar
¶ Maximal dual bound violation for \(\barX\) in the interiorpoint solution.

dinfitem.sol_itr_dviolcon
¶ Maximal dual bound violation for \(x^c\) in the interiorpoint solution.

dinfitem.sol_itr_dviolcones
¶ Maximal dual violation for dual conic constraints in the interiorpoint solution.

dinfitem.sol_itr_dviolvar
¶ Maximal dual bound violation for \(x^x\) in the interiorpoint solution.

dinfitem.sol_itr_nrm_bars
¶ Infinity norm of \(\barS\) in the interiorpoint solution.

dinfitem.sol_itr_nrm_barx
¶ Infinity norm of \(\barX\) in the interiorpoint solution.

dinfitem.sol_itr_nrm_slc
¶ Infinity norm of \(s_l^c\) in the interiorpoint solution.

dinfitem.sol_itr_nrm_slx
¶ Infinity norm of \(s_l^x\) in the interiorpoint solution.

dinfitem.sol_itr_nrm_snx
¶ Infinity norm of \(s_n^x\) in the interiorpoint solution.

dinfitem.sol_itr_nrm_suc
¶ Infinity norm of \(s_u^c\) in the interiorpoint solution.

dinfitem.sol_itr_nrm_sux
¶ Infinity norm of \(s_u^X\) in the interiorpoint solution.

dinfitem.sol_itr_nrm_xc
¶ Infinity norm of \(x^c\) in the interiorpoint solution.

dinfitem.sol_itr_nrm_xx
¶ Infinity norm of \(x^x\) in the interiorpoint solution.

dinfitem.sol_itr_nrm_y
¶ Infinity norm of \(y\) in the interiorpoint solution.

dinfitem.sol_itr_primal_obj
¶ Primal objective value of the interiorpoint solution.

dinfitem.sol_itr_pviolbarvar
¶ Maximal primal bound violation for \(\barX\) in the interiorpoint solution.

dinfitem.sol_itr_pviolcon
¶ Maximal primal bound violation for \(x^c\) in the interiorpoint solution.

dinfitem.sol_itr_pviolcones
¶ Maximal primal violation for primal conic constraints in the interiorpoint solution.

dinfitem.sol_itr_pviolvar
¶ Maximal primal bound violation for \(x^x\) in the interiorpoint solution.

dinfitem.to_conic_time
¶ Time spent in the last to conic reformulation.


liinfitem
¶ Long integer information items.

liinfitem.bi_clean_dual_deg_iter
¶ Number of dual degenerate clean iterations performed in the basis identification.

liinfitem.bi_clean_dual_iter
¶ Number of dual clean iterations performed in the basis identification.

liinfitem.bi_clean_primal_deg_iter
¶ Number of primal degenerate clean iterations performed in the basis identification.

liinfitem.bi_clean_primal_iter
¶ Number of primal clean iterations performed in the basis identification.

liinfitem.bi_dual_iter
¶ Number of dual pivots performed in the basis identification.

liinfitem.bi_primal_iter
¶ Number of primal pivots performed in the basis identification.

liinfitem.intpnt_factor_num_nz
¶ Number of nonzeros in factorization.

liinfitem.mio_intpnt_iter
¶ Number of interiorpoint iterations performed by the mixedinteger optimizer.

liinfitem.mio_presolved_anz
¶ Number of nonzero entries in the constraint matrix of presolved problem.

liinfitem.mio_sim_maxiter_setbacks
¶ Number of times the the simplex optimizer has hit the maximum iteration limit when reoptimizing.

liinfitem.mio_simplex_iter
¶ Number of simplex iterations performed by the mixedinteger optimizer.

liinfitem.rd_numanz
¶ Number of nonzeros in A that is read.

liinfitem.rd_numqnz
¶ Number of Q nonzeros.


iinfitem
¶ Integer information items.

iinfitem.ana_pro_num_con
¶ Number of constraints in the problem.
This value is set by
Task.analyzeproblem
.

iinfitem.ana_pro_num_con_eq
¶ Number of equality constraints.
This value is set by
Task.analyzeproblem
.

iinfitem.ana_pro_num_con_fr
¶ Number of unbounded constraints.
This value is set by
Task.analyzeproblem
.

iinfitem.ana_pro_num_con_lo
¶ Number of constraints with a lower bound and an infinite upper bound.
This value is set by
Task.analyzeproblem
.

iinfitem.ana_pro_num_con_ra
¶ Number of constraints with finite lower and upper bounds.
This value is set by
Task.analyzeproblem
.

iinfitem.ana_pro_num_con_up
¶ Number of constraints with an upper bound and an infinite lower bound.
This value is set by
Task.analyzeproblem
.

iinfitem.ana_pro_num_var
¶ Number of variables in the problem.
This value is set by
Task.analyzeproblem
.

iinfitem.ana_pro_num_var_bin
¶ Number of binary (01) variables.
This value is set by
Task.analyzeproblem
.

iinfitem.ana_pro_num_var_cont
¶ Number of continuous variables.
This value is set by
Task.analyzeproblem
.

iinfitem.ana_pro_num_var_eq
¶ Number of fixed variables.
This value is set by
Task.analyzeproblem
.

iinfitem.ana_pro_num_var_fr
¶ Number of free variables.
This value is set by
Task.analyzeproblem
.

iinfitem.ana_pro_num_var_int
¶ Number of general integer variables.
This value is set by
Task.analyzeproblem
.

iinfitem.ana_pro_num_var_lo
¶ Number of variables with a lower bound and an infinite upper bound.
This value is set by
Task.analyzeproblem
.

iinfitem.ana_pro_num_var_ra
¶ Number of variables with finite lower and upper bounds.
This value is set by
Task.analyzeproblem
.

iinfitem.ana_pro_num_var_up
¶ Number of variables with an upper bound and an infinite lower bound. This value is set by
This value is set by
Task.analyzeproblem
.

iinfitem.intpnt_factor_dim_dense
¶ Dimension of the dense sub system in factorization.

iinfitem.intpnt_iter
¶ Number of interiorpoint iterations since invoking the interiorpoint optimizer.

iinfitem.intpnt_num_threads
¶ Number of threads that the interiorpoint optimizer is using.

iinfitem.intpnt_solve_dual
¶ Nonzero if the interiorpoint optimizer is solving the dual problem.

iinfitem.mio_absgap_satisfied
¶ Nonzero if absolute gap is within tolerances.

iinfitem.mio_clique_table_size
¶ Size of the clique table.

iinfitem.mio_construct_num_roundings
¶ Number of values in the integer solution that is rounded to an integer value.

iinfitem.mio_construct_solution
¶ If this item has the value 0, then MOSEK did not try to construct an initial integer feasible solution. If the item has a positive value, then MOSEK successfully constructed an initial integer feasible solution.

iinfitem.mio_initial_solution
¶ Is nonzero if an initial integer solution is specified.

iinfitem.mio_near_absgap_satisfied
¶ Nonzero if absolute gap is within relaxed tolerances.

iinfitem.mio_near_relgap_satisfied
¶ Nonzero if relative gap is within relaxed tolerances.

iinfitem.mio_node_depth
¶ Depth of the last node solved.

iinfitem.mio_num_active_nodes
¶ Number of active branch bound nodes.

iinfitem.mio_num_branch
¶ Number of branches performed during the optimization.

iinfitem.mio_num_clique_cuts
¶ Number of clique cuts.

iinfitem.mio_num_cmir_cuts
¶ Number of Complemented Mixed Integer Rounding (CMIR) cuts.

iinfitem.mio_num_gomory_cuts
¶ Number of Gomory cuts.

iinfitem.mio_num_implied_bound_cuts
¶ Number of implied bound cuts.

iinfitem.mio_num_int_solutions
¶ Number of integer feasible solutions that has been found.

iinfitem.mio_num_knapsack_cover_cuts
¶ Number of clique cuts.

iinfitem.mio_num_relax
¶ Number of relaxations solved during the optimization.

iinfitem.mio_num_repeated_presolve
¶ Number of times presolve was repeated at root.

iinfitem.mio_numcon
¶ Number of constraints in the problem solved by the mixedinteger optimizer.

iinfitem.mio_numint
¶ Number of integer variables in the problem solved be the mixedinteger optimizer.

iinfitem.mio_numvar
¶ Number of variables in the problem solved by the mixedinteger optimizer.

iinfitem.mio_obj_bound_defined
¶ Nonzero if a valid objective bound has been found, otherwise zero.

iinfitem.mio_presolved_numbin
¶ Number of binary variables in the problem solved be the mixedinteger optimizer.

iinfitem.mio_presolved_numcon
¶ Number of constraints in the presolved problem.

iinfitem.mio_presolved_numcont
¶ Number of continuous variables in the problem solved be the mixedinteger optimizer.

iinfitem.mio_presolved_numint
¶ Number of integer variables in the presolved problem.

iinfitem.mio_presolved_numvar
¶ Number of variables in the presolved problem.

iinfitem.mio_relgap_satisfied
¶ Nonzero if relative gap is within tolerances.

iinfitem.mio_total_num_cuts
¶ Total number of cuts generated by the mixedinteger optimizer.

iinfitem.mio_user_obj_cut
¶ If it is nonzero, then the objective cut is used.

iinfitem.opt_numcon
¶ Number of constraints in the problem solved when the optimizer is called.

iinfitem.opt_numvar
¶ Number of variables in the problem solved when the optimizer is called

iinfitem.optimize_response
¶ The response code returned by optimize.

iinfitem.rd_numbarvar
¶ Number of variables read.

iinfitem.rd_numcon
¶ Number of constraints read.

iinfitem.rd_numcone
¶ Number of conic constraints read.

iinfitem.rd_numintvar
¶ Number of integerconstrained variables read.

iinfitem.rd_numq
¶ Number of nonempty Q matrices read.

iinfitem.rd_numvar
¶ Number of variables read.

iinfitem.rd_protype
¶ Problem type.

iinfitem.sim_dual_deg_iter
¶ The number of dual degenerate iterations.

iinfitem.sim_dual_hotstart
¶ If 1 then the dual simplex algorithm is solving from an advanced basis.

iinfitem.sim_dual_hotstart_lu
¶ If 1 then a valid basis factorization of full rank was located and used by the dual simplex algorithm.

iinfitem.sim_dual_inf_iter
¶ The number of iterations taken with dual infeasibility.

iinfitem.sim_dual_iter
¶ Number of dual simplex iterations during the last optimization.

iinfitem.sim_numcon
¶ Number of constraints in the problem solved by the simplex optimizer.

iinfitem.sim_numvar
¶ Number of variables in the problem solved by the simplex optimizer.

iinfitem.sim_primal_deg_iter
¶ The number of primal degenerate iterations.

iinfitem.sim_primal_hotstart
¶ If 1 then the primal simplex algorithm is solving from an advanced basis.

iinfitem.sim_primal_hotstart_lu
¶ If 1 then a valid basis factorization of full rank was located and used by the primal simplex algorithm.

iinfitem.sim_primal_inf_iter
¶ The number of iterations taken with primal infeasibility.

iinfitem.sim_primal_iter
¶ Number of primal simplex iterations during the last optimization.

iinfitem.sim_solve_dual
¶ Is nonzero if dual problem is solved.

iinfitem.sol_bas_prosta
¶ Problem status of the basic solution. Updated after each optimization.

iinfitem.sol_bas_solsta
¶ Solution status of the basic solution. Updated after each optimization.

iinfitem.sol_itg_prosta
¶ Problem status of the integer solution. Updated after each optimization.

iinfitem.sol_itg_solsta
¶ Solution status of the integer solution. Updated after each optimization.

iinfitem.sol_itr_prosta
¶ Problem status of the interiorpoint solution. Updated after each optimization.

iinfitem.sol_itr_solsta
¶ Solution status of the interiorpoint solution. Updated after each optimization.

iinfitem.sto_num_a_realloc
¶ Number of times the storage for storing \(A\) has been changed. A large value may indicates that memory fragmentation may occur.


inftype
¶ Information item types

inftype.dou_type
¶ Is a double information type.

inftype.int_type
¶ Is an integer.

inftype.lint_type
¶ Is a long integer.


iomode
¶ Input/output modes

iomode.read
¶ The file is readonly.

iomode.write
¶ The file is writeonly. If the file exists then it is truncated when it is opened. Otherwise it is created when it is opened.

iomode.readwrite
¶ The file is to read and written.


branchdir
¶ Specifies the branching direction.

branchdir.free
¶ The mixedinteger optimizer decides which branch to choose.

branchdir.up
¶ The mixedinteger optimizer always chooses the up branch first.

branchdir.down
¶ The mixedinteger optimizer always chooses the down branch first.

branchdir.near
¶ Branch in direction nearest to selected fractional variable.

branchdir.far
¶ Branch in direction farthest from selected fractional variable.

branchdir.root_lp
¶ Chose direction based on root lp value of selected variable.

branchdir.guided
¶ Branch in direction of current incumbent.

branchdir.pseudocost
¶ Branch based on the pseudocost of the variable.


miocontsoltype
¶ Continuous mixedinteger solution type

miocontsoltype.none
¶ No interiorpoint or basic solution are reported when the mixedinteger optimizer is used.

miocontsoltype.root
¶ The reported interiorpoint and basic solutions are a solution to the root node problem when mixedinteger optimizer is used.

miocontsoltype.itg
¶ The reported interiorpoint and basic solutions are a solution to the problem with all integer variables fixed at the value they have in the integer solution. A solution is only reported in case the problem has a primal feasible solution.

miocontsoltype.itg_rel
¶ In case the problem is primal feasible then the reported interiorpoint and basic solutions are a solution to the problem with all integer variables fixed at the value they have in the integer solution. If the problem is primal infeasible, then the solution to the root node problem is reported.


miomode
¶ Integer restrictions

miomode.ignored
¶ The integer constraints are ignored and the problem is solved as a continuous problem.

miomode.satisfied
¶ Integer restrictions should be satisfied.


mionodeseltype
¶ Mixedinteger node selection types

mionodeseltype.free
¶ The optimizer decides the node selection strategy.

mionodeseltype.first
¶ The optimizer employs a depth first node selection strategy.

mionodeseltype.best
¶ The optimizer employs a best bound node selection strategy.

mionodeseltype.worst
¶ The optimizer employs a worst bound node selection strategy.

mionodeseltype.hybrid
¶ The optimizer employs a hybrid strategy.

mionodeseltype.pseudo
¶ The optimizer employs selects the node based on a pseudo cost estimate.


mpsformat
¶ MPS file format type

mpsformat.strict
¶ It is assumed that the input file satisfies the MPS format strictly.

mpsformat.relaxed
¶ It is assumed that the input file satisfies a slightly relaxed version of the MPS format.

mpsformat.free
¶ It is assumed that the input file satisfies the free MPS format. This implies that spaces are not allowed in names. Otherwise the format is free.

mpsformat.cplex
¶ The CPLEX compatible version of the MPS format is employed.


objsense
¶ Objective sense types

objsense.minimize
¶ The problem should be minimized.

objsense.maximize
¶ The problem should be maximized.


optimizertype
¶ Optimizer types

optimizertype.conic
¶ The optimizer for problems having conic constraints.

optimizertype.dual_simplex
¶ The dual simplex optimizer is used.

optimizertype.free
¶ The optimizer is chosen automatically.

optimizertype.free_simplex
¶ One of the simplex optimizers is used.

optimizertype.intpnt
¶ The interiorpoint optimizer is used.

optimizertype.mixed_int
¶ The mixedinteger optimizer.

optimizertype.primal_simplex
¶ The primal simplex optimizer is used.


orderingtype
¶ Ordering strategies

orderingtype.free
¶ The ordering method is chosen automatically.

orderingtype.appminloc
¶ Approximate minimum local fillin ordering is employed.

orderingtype.experimental
¶ This option should not be used.

orderingtype.try_graphpar
¶ Always try the graph partitioning based ordering.

orderingtype.force_graphpar
¶ Always use the graph partitioning based ordering even if it is worse than the approximate minimum local fill ordering.

orderingtype.none
¶ No ordering is used.


presolvemode
¶ Presolve method.

presolvemode.off
¶ The problem is not presolved before it is optimized.

presolvemode.on
¶ The problem is presolved before it is optimized.

presolvemode.free
¶ It is decided automatically whether to presolve before the problem is optimized.


parametertype
¶ Parameter type

parametertype.invalid_type
¶ Not a valid parameter.

parametertype.dou_type
¶ Is a double parameter.

parametertype.int_type
¶ Is an integer parameter.

parametertype.str_type
¶ Is a string parameter.


problemitem
¶ Problem data items

problemitem.var
¶ Item is a variable.

problemitem.con
¶ Item is a constraint.

problemitem.cone
¶ Item is a cone.


problemtype
¶ Problem types

problemtype.lo
¶ The problem is a linear optimization problem.

problemtype.qo
¶ The problem is a quadratic optimization problem.

problemtype.qcqo
¶ The problem is a quadratically constrained optimization problem.

problemtype.geco
¶ General convex optimization.

problemtype.conic
¶ A conic optimization.

problemtype.mixed
¶ General nonlinear constraints and conic constraints. This combination can not be solved by MOSEK.


prosta
¶ Problem status keys

prosta.unknown
¶ Unknown problem status.

prosta.prim_and_dual_feas
¶ The problem is primal and dual feasible.

prosta.prim_feas
¶ The problem is primal feasible.

prosta.dual_feas
¶ The problem is dual feasible.

prosta.near_prim_and_dual_feas
¶ The problem is at least nearly primal and dual feasible.

prosta.near_prim_feas
¶ The problem is at least nearly primal feasible.

prosta.near_dual_feas
¶ The problem is at least nearly dual feasible.

prosta.prim_infeas
¶ The problem is primal infeasible.

prosta.dual_infeas
¶ The problem is dual infeasible.

prosta.prim_and_dual_infeas
¶ The problem is primal and dual infeasible.

prosta.ill_posed
¶ The problem is illposed. For example, it may be primal and dual feasible but have a positive duality gap.

prosta.prim_infeas_or_unbounded
¶ The problem is either primal infeasible or unbounded. This may occur for mixedinteger problems.


xmlwriteroutputtype
¶ XML writer output mode

xmlwriteroutputtype.row
¶ Write in row order.

xmlwriteroutputtype.col
¶ Write in column order.


rescodetype
¶ Response code type

rescodetype.ok
¶ The response code is OK.

rescodetype.wrn
¶ The response code is a warning.

rescodetype.trm
¶ The response code is an optimizer termination status.

rescodetype.err
¶ The response code is an error.

rescodetype.unk
¶ The response code does not belong to any class.


scalingtype
¶ Scaling type

scalingtype.free
¶ The optimizer chooses the scaling heuristic.

scalingtype.none
¶ No scaling is performed.

scalingtype.moderate
¶ A conservative scaling is performed.

scalingtype.aggressive
¶ A very aggressive scaling is performed.


scalingmethod
¶ Scaling method

scalingmethod.pow2
¶ Scales only with power of 2 leaving the mantissa untouched.

scalingmethod.free
¶ The optimizer chooses the scaling heuristic.


sensitivitytype
¶ Sensitivity types

sensitivitytype.basis
¶ Basis sensitivity analysis is performed.

sensitivitytype.optimal_partition
¶ Optimal partition sensitivity analysis is performed.


simseltype
¶ Simplex selection strategy

simseltype.free
¶ The optimizer chooses the pricing strategy.

simseltype.full
¶ The optimizer uses full pricing.

simseltype.ase
¶ The optimizer uses approximate steepestedge pricing.

simseltype.devex
¶ The optimizer uses devex steepestedge pricing (or if it is not available an approximate steepedge selection).

simseltype.se
¶ The optimizer uses steepestedge selection (or if it is not available an approximate steepedge selection).

simseltype.partial
¶ The optimizer uses a partial selection approach. The approach is usually beneficial if the number of variables is much larger than the number of constraints.


solitem
¶ Solution items

solitem.xc
¶ Solution for the constraints.

solitem.xx
¶ Variable solution.

solitem.y
¶ Lagrange multipliers for equations.

solitem.slc
¶ Lagrange multipliers for lower bounds on the constraints.

solitem.suc
¶ Lagrange multipliers for upper bounds on the constraints.

solitem.slx
¶ Lagrange multipliers for lower bounds on the variables.

solitem.sux
¶ Lagrange multipliers for upper bounds on the variables.

solitem.snx
¶ Lagrange multipliers corresponding to the conic constraints on the variables.


solsta
¶ Solution status keys

solsta.unknown
¶ Status of the solution is unknown.

solsta.optimal
¶ The solution is optimal.

solsta.prim_feas
¶ The solution is primal feasible.

solsta.dual_feas
¶ The solution is dual feasible.

solsta.prim_and_dual_feas
¶ The solution is both primal and dual feasible.

solsta.near_optimal
¶ The solution is nearly optimal.

solsta.near_prim_feas
¶ The solution is nearly primal feasible.

solsta.near_dual_feas
¶ The solution is nearly dual feasible.

solsta.near_prim_and_dual_feas
¶ The solution is nearly both primal and dual feasible.

solsta.prim_infeas_cer
¶ The solution is a certificate of primal infeasibility.

solsta.dual_infeas_cer
¶ The solution is a certificate of dual infeasibility.

solsta.near_prim_infeas_cer
¶ The solution is almost a certificate of primal infeasibility.

solsta.near_dual_infeas_cer
¶ The solution is almost a certificate of dual infeasibility.

solsta.prim_illposed_cer
¶ The solution is a certificate that the primal problem is illposed.

solsta.dual_illposed_cer
¶ The solution is a certificate that the dual problem is illposed.

solsta.integer_optimal
¶ The primal solution is integer optimal.

solsta.near_integer_optimal
¶ The primal solution is near integer optimal.


soltype
¶ Solution types

soltype.bas
¶ The basic solution.

soltype.itr
¶ The interior solution.

soltype.itg
¶ The integer solution.


solveform
¶ Solve primal or dual form

solveform.free
¶ The optimizer is free to solve either the primal or the dual problem.

solveform.primal
¶ The optimizer should solve the primal problem.

solveform.dual
¶ The optimizer should solve the dual problem.


stakey
¶ Status keys

stakey.unk
¶ The status for the constraint or variable is unknown.

stakey.bas
¶ The constraint or variable is in the basis.

stakey.supbas
¶ The constraint or variable is super basic.

stakey.low
¶ The constraint or variable is at its lower bound.

stakey.upr
¶ The constraint or variable is at its upper bound.

stakey.fix
¶ The constraint or variable is fixed.

stakey.inf
¶ The constraint or variable is infeasible in the bounds.


startpointtype
¶ Starting point types

startpointtype.free
¶ The starting point is chosen automatically.

startpointtype.guess
¶ The optimizer guesses a starting point.

startpointtype.constant
¶ The optimizer constructs a starting point by assigning a constant value to all primal and dual variables. This starting point is normally robust.

startpointtype.satisfy_bounds
¶ The starting point is chosen to satisfy all the simple bounds on nonlinear variables. If this starting point is employed, then more care than usual should employed when choosing the bounds on the nonlinear variables. In particular very tight bounds should be avoided.


streamtype
¶ Stream types

streamtype.log
¶ Log stream. Contains the aggregated contents of all other streams. This means that a message written to any other stream will also be written to this stream.

streamtype.msg
¶ Message stream. Log information relating to performance and progress of the optimization is written to this stream.

streamtype.err
¶ Error stream. Error messages are written to this stream.

streamtype.wrn
¶ Warning stream. Warning messages are written to this stream.
