An interface for the MOSEK solver.
MOSEK() # S4 method for MOSEK mip_capable(solver) # S4 method for MOSEK import_solver(solver) # S4 method for MOSEK name(x) # S4 method for MOSEK,Problem accepts(object, problem) # S4 method for MOSEK block_format(object, problem, constraints, exp_cone_order = NA) # S4 method for MOSEK,Problem perform(object, problem) # S4 method for MOSEK solve_via_data( object, data, warm_start, verbose, feastol, reltol, abstol, num_iter, solver_opts, solver_cache ) # S4 method for MOSEK,ANY,ANY invert(object, solution, inverse_data)
A MOSEK object.
A Problem object.
A list of Constraint objects for which coefficient andd offset data ("G", "h" respectively) is needed
A parameter that is only used when a Constraint object describes membership in the exponential cone.
Data generated via an apply call.
A boolean of whether to warm start the solver.
A boolean of whether to enable solver verbosity.
The feasible tolerance.
The relative tolerance.
The absolute tolerance.
The maximum number of iterations.
A list of Solver specific options
Cache for the solver.
The raw solution returned by the solver.
A list containing data necessary for the inversion.
mip_capable(MOSEK): Can the solver handle mixed-integer programs?
import_solver(MOSEK): Imports the solver.
name(MOSEK): Returns the name of the solver.
accepts(object = MOSEK, problem = Problem): Can MOSEK solve the problem?
block_format(MOSEK): Returns a large matrix "coeff" and a vector of constants "offset" such
that every Constraint in "constraints" holds at z in R^n iff
"coeff" * z <=_K offset", where K is a product of cones supported by MOSEK
and CVXR (zero cone, nonnegative orthant, second order cone, exponential cone). The
nature of K is inferred later by accessing the data in "lengths" and "ids".
perform(object = MOSEK, problem = Problem): Returns a new problem and data for inverting the new solution.
solve_via_data(MOSEK): Solve a problem represented by data returned from apply.
invert(object = MOSEK, solution = ANY, inverse_data = ANY): Returns the solution to the original problem given the inverse_data.