Solution, primal and dual (if available, NA otherwise). Variable reduced cost, if available ( NA otherwise).Ī list with two vectors each containing the values of theĪuxiliary variable associated with the respective constraint at If the control parameter is set toįALSE it will return the GLPK status codes. (the default) then it will return 0 for the optimal solution beingįound, and non-zero otherwise. If the control parameter canonicalize_status is set The value of the objective function at the optimumĪn integer with status information about the solution
LINEAR PROGRAMMING SOLVER CODE
Whether to canonicalize GLPK status codes (on success Rglpk_solve_LP() returns code 0) orĪ list containing the optimal solution, with the following components. Time limit in milliseconds of call to optimizer.
LINEAR PROGRAMMING SOLVER MANUAL
Programming Kit Reference Manual for further details. See the respective method section of the GNU Linear The control argument can be used to set GLPK's many ( simple_triplet_matrix) as provided by the slam Matrix mat and obj may be sparse arrays or matrices R interface packages which port all low level C routines Provides a high level solver function using the low level C interface See *Details*.Ī list of control parameters (overruling those specified in TRUE means that the objective is to maximize the objectiveįunction, FALSE (default) means to minimize it.Ī list of parameters to the solver. Recycled as needed.Ī logical giving the direction of the optimization. The default forĮach variable is a bound between 0 and Inf.Ī character vector indicating the types of the objective Upper and lower containing the indices andĬorresponding bounds of the objective variables. Strict inequalities are handled the sameĪ numeric vector representing the right hand side of the constraints. Note, however, that the GLPK API only allows for
The optimization problem is unconstrained then a matrix of dimensionĠ times the number of objective variables is required.Ī character vector with the directions of the constraints.įor a nonzero number of constraints each element must be one of )Ī numeric vector representing the objective coefficients.Ī numeric vector or a (sparse) matrix of constraint coefficients. Rglpk_solve_LP ( obj, mat, dir, rhs, bounds = NULL, types = NULL, max = FALSE, control = list ().