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.