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mosek.iinfitem.ana_pro_num_con
Number of constraints in the problem.
This value is set by mosek.Task.analyzeproblem.
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mosek.iinfitem.ana_pro_num_con_eq
Number of equality constraints.
This value is set by mosek.Task.analyzeproblem.
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mosek.iinfitem.ana_pro_num_con_fr
Number of unbounded constraints.
This value is set by mosek.Task.analyzeproblem.
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mosek.iinfitem.ana_pro_num_con_lo
Number of constraints with a lower bound and an infinite upper bound.
This value is set by mosek.Task.analyzeproblem.
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mosek.iinfitem.ana_pro_num_con_ra
Number of constraints with finite lower and upper bounds.
This value is set by mosek.Task.analyzeproblem.
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mosek.iinfitem.ana_pro_num_con_up
Number of constraints with an upper bound and an infinite lower bound.
This value is set by mosek.Task.analyzeproblem.
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mosek.iinfitem.ana_pro_num_var
Number of variables in the problem.
This value is set by mosek.Task.analyzeproblem.
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mosek.iinfitem.ana_pro_num_var_bin
Number of binary (0-1) variables.
This value is set by mosek.Task.analyzeproblem.
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mosek.iinfitem.ana_pro_num_var_cont
Number of continuous variables.
This value is set by mosek.Task.analyzeproblem.
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mosek.iinfitem.ana_pro_num_var_eq
Number of fixed variables.
This value is set by mosek.Task.analyzeproblem.
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mosek.iinfitem.ana_pro_num_var_fr
Number of free variables.
This value is set by mosek.Task.analyzeproblem.
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mosek.iinfitem.ana_pro_num_var_int
Number of general integer variables.
This value is set by mosek.Task.analyzeproblem.
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mosek.iinfitem.ana_pro_num_var_lo
Number of variables with a lower bound and an infinite upper bound.
This value is set by mosek.Task.analyzeproblem.
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mosek.iinfitem.ana_pro_num_var_ra
Number of variables with finite lower and upper bounds.
This value is set by mosek.Task.analyzeproblem.
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mosek.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 mosek.Task.analyzeproblem.
- mosek.iinfitem.cache_size_l1
L1 cache size used.
- mosek.iinfitem.cache_size_l2
L2 cache size used.
- mosek.iinfitem.concurrent_fastest_optimizer
The type of the optimizer that finished first in a concurrent optimization.
- mosek.iinfitem.cpu_type
The type of cpu detected.
- mosek.iinfitem.intpnt_factor_num_offcol
Number of columns in the constraint matrix (or Jacobian) that has an offending structure.
- mosek.iinfitem.intpnt_iter
Number of interior-point iterations since invoking the interior-point optimizer.
- mosek.iinfitem.intpnt_num_threads
Number of threads that the interior-point optimizer is using.
- mosek.iinfitem.intpnt_solve_dual
Non-zero if the interior-point optimizer is solving the dual problem.
- mosek.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.
- mosek.iinfitem.mio_initial_solution
Is non-zero if an initial integer solution is specified.
- mosek.iinfitem.mio_num_active_nodes
Number of active nodes in the branch and bound tree.
- mosek.iinfitem.mio_num_branch
Number of branches performed during the optimization.
- mosek.iinfitem.mio_num_cuts
Number of cuts generated by the mixed-integer optimizer.
- mosek.iinfitem.mio_num_int_solutions
Number of integer feasible solutions that has been found.
- mosek.iinfitem.mio_num_relax
Number of relaxations solved during the optimization.
- mosek.iinfitem.mio_numcon
Number of constraints in the problem solved be the mixed-integer optimizer.
- mosek.iinfitem.mio_numint
Number of integer variables in the problem solved be the mixed-integer optimizer.
- mosek.iinfitem.mio_numvar
Number of variables in the problem solved be the mixed-integer optimizer.
- mosek.iinfitem.mio_total_num_basis_cuts
Number of basis cuts.
- mosek.iinfitem.mio_total_num_branch
Number of branches performed during the optimization.
- mosek.iinfitem.mio_total_num_cardgub_cuts
Number of cardgub cuts.
- mosek.iinfitem.mio_total_num_clique_cuts
Number of clique cuts.
- mosek.iinfitem.mio_total_num_coef_redc_cuts
Number of coef. redc. cuts.
- mosek.iinfitem.mio_total_num_contra_cuts
Number of contra cuts.
- mosek.iinfitem.mio_total_num_cuts
Total number of cuts generated by the mixed-integer optimizer.
- mosek.iinfitem.mio_total_num_disagg_cuts
Number of diasagg cuts.
- mosek.iinfitem.mio_total_num_flow_cover_cuts
Number of flow cover cuts.
- mosek.iinfitem.mio_total_num_gcd_cuts
Number of gcd cuts.
- mosek.iinfitem.mio_total_num_gomory_cuts
Number of Gomory cuts.
- mosek.iinfitem.mio_total_num_gub_cover_cuts
Number of GUB cover cuts.
- mosek.iinfitem.mio_total_num_knapsur_cover_cuts
Number of knapsack cover cuts.
- mosek.iinfitem.mio_total_num_lattice_cuts
Number of lattice cuts.
- mosek.iinfitem.mio_total_num_lift_cuts
Number of lift cuts.
- mosek.iinfitem.mio_total_num_obj_cuts
Number of obj cuts.
- mosek.iinfitem.mio_total_num_plan_loc_cuts
Number of loc cuts.
- mosek.iinfitem.mio_total_num_relax
Number of relaxations solved during the optimization.
- mosek.iinfitem.mio_user_obj_cut
If it is non-zero, then the objective cut is used.
- mosek.iinfitem.opt_numcon
Number of constraints in the problem solved when the optimizer is called.
- mosek.iinfitem.opt_numvar
Number of variables in the problem solved when the optimizer is called
- mosek.iinfitem.optimize_response
The reponse code returned by optimize.
- mosek.iinfitem.rd_numcon
Number of constraints read.
- mosek.iinfitem.rd_numcone
Number of conic constraints read.
- mosek.iinfitem.rd_numintvar
Number of integer-constrained variables read.
- mosek.iinfitem.rd_numq
Number of nonempty Q matrices read.
- mosek.iinfitem.rd_numvar
Number of variables read.
- mosek.iinfitem.rd_protype
Problem type.
- mosek.iinfitem.sim_dual_deg_iter
The number of dual degenerate iterations.
- mosek.iinfitem.sim_dual_hotstart
If 1 then the dual simplex algorithm is solving from an advanced basis.
- mosek.iinfitem.sim_dual_hotstart_lu
If 1 then a valid basis factorization of full rank was located and used by the dual simplex algorithm.
- mosek.iinfitem.sim_dual_inf_iter
The number of iterations taken with dual infeasibility.
- mosek.iinfitem.sim_dual_iter
Number of dual simplex iterations during the last optimization.
- mosek.iinfitem.sim_network_dual_deg_iter
The number of dual network degenerate iterations.
- mosek.iinfitem.sim_network_dual_hotstart
If 1 then the dual network simplex algorithm is solving from an advanced basis.
- mosek.iinfitem.sim_network_dual_hotstart_lu
If 1 then a valid basis factorization of full rank was located and used by the dual network simplex algorithm.
- mosek.iinfitem.sim_network_dual_inf_iter
The number of iterations taken with dual infeasibility in the network optimizer.
- mosek.iinfitem.sim_network_dual_iter
Number of dual network simplex iterations during the last optimization.
- mosek.iinfitem.sim_network_primal_deg_iter
The number of primal network degenerate iterations.
- mosek.iinfitem.sim_network_primal_hotstart
If 1 then the primal network simplex algorithm is solving from an advanced basis.
- mosek.iinfitem.sim_network_primal_hotstart_lu
If 1 then a valid basis factorization of full rank was located and used by the primal network simplex algorithm.
- mosek.iinfitem.sim_network_primal_inf_iter
The number of iterations taken with primal infeasibility in the network optimizer.
- mosek.iinfitem.sim_network_primal_iter
Number of primal network simplex iterations during the last optimization.
- mosek.iinfitem.sim_numcon
Number of constraints in the problem solved by the simplex optimizer.
- mosek.iinfitem.sim_numvar
Number of variables in the problem solved by the simplex optimizer.
- mosek.iinfitem.sim_primal_deg_iter
The number of primal degenerate iterations.
- mosek.iinfitem.sim_primal_dual_deg_iter
The number of degenerate major iterations taken by the primal dual simplex algorithm.
- mosek.iinfitem.sim_primal_dual_hotstart
If 1 then the primal dual simplex algorithm is solving from an advanced basis.
- mosek.iinfitem.sim_primal_dual_hotstart_lu
If 1 then a valid basis factorization of full rank was located and used by the primal dual simplex algorithm.
- mosek.iinfitem.sim_primal_dual_inf_iter
The number of master iterations with dual infeasibility taken by the primal dual simplex algorithm.
- mosek.iinfitem.sim_primal_dual_iter
Number of primal dual simplex iterations during the last optimization.
- mosek.iinfitem.sim_primal_hotstart
If 1 then the primal simplex algorithm is solving from an advanced basis.
- mosek.iinfitem.sim_primal_hotstart_lu
If 1 then a valid basis factorization of full rank was located and used by the primal simplex algorithm.
- mosek.iinfitem.sim_primal_inf_iter
The number of iterations taken with primal infeasibility.
- mosek.iinfitem.sim_primal_iter
Number of primal simplex iterations during the last optimization.
- mosek.iinfitem.sim_solve_dual
Is non-zero if dual problem is solved.
- mosek.iinfitem.sol_bas_prosta
Problem status of the basic solution. Updated after each optimization.
- mosek.iinfitem.sol_bas_solsta
Solution status of the basic solution. Updated after each optimization.
- mosek.iinfitem.sol_int_prosta
Problem status of the integer solution. Updated after each optimization.
- mosek.iinfitem.sol_int_solsta
Solution status of the integer solution. Updated after each optimization.
- mosek.iinfitem.sol_itr_prosta
Problem status of the interior-point solution. Updated after each optimization.
- mosek.iinfitem.sol_itr_solsta
Solution status of the interior-point solution. Updated after each optimization.
- mosek.iinfitem.sto_num_a_cache_flushes
Number of times the cache of A elements is flushed. A large number implies that maxnumanz is too small as well as an inefficient usage of MOSEK.
- mosek.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.
- mosek.iinfitem.sto_num_a_transposes
Number of times the A matrix is transposed. A large number implies that maxnumanz is too small or an inefficient usage of MOSEK. This will occur in particular if the code alternate between accessing rows and columns of A.