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