These functions are used to access data from an
OptimizationProblem-class object.
nrow(x) # S4 method for OptimizationProblem nrow(x) ncol(x) # S4 method for OptimizationProblem ncol(x) ncell(x) # S4 method for OptimizationProblem ncell(x) modelsense(x) # S4 method for OptimizationProblem modelsense(x) vtype(x) # S4 method for OptimizationProblem vtype(x) obj(x) # S4 method for OptimizationProblem obj(x) A(x) # S4 method for OptimizationProblem A(x) rhs(x) # S4 method for OptimizationProblem rhs(x) sense(x) # S4 method for OptimizationProblem sense(x) lb(x) # S4 method for OptimizationProblem lb(x) ub(x) # S4 method for OptimizationProblem ub(x) col_ids(x) # S4 method for OptimizationProblem col_ids(x) row_ids(x) # S4 method for OptimizationProblem row_ids(x) compressed_formulation(x) # S4 method for OptimizationProblem compressed_formulation(x)
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dgCMatrix-class, numeric vector,
numeric vector, or scalar integer depending on the method
used.
The functions return the following data:
integer number of rows (constraints).
integer number of columns (decision variables).
integer number of cells.
character describing if the problem is to be
maximized ("max") or minimized ("min").
character describing the type of each decision variable:
binary ("B"), semi-continuous ("S"), or continuous
("C")
numeric vector specifying the objective function.
dgCMatrix-class matrix object defining the
problem matrix.
numeric vector with right-hand-side linear constraints
character vector with the senses of the linear
constraints ("<=", ">=", "=").
numeric lower bound for each decision variable. Missing data
values (NA) indicate no lower bound for a given variable.
numeric upper bounds for each decision variable. Missing
data values (NA) indicate no upper bound for a given variable.
integer number of planning units in
the problem.
integer number of features
the problem.