A variable can either be a name or an indexed name. See examples.
Usage
add_variable(.model, .variable, ..., type = "continuous", lb = -Inf, ub = Inf)
add_variable_(
.model,
.variable,
...,
type = "continuous",
lb = -Inf,
ub = Inf,
.dots
)
Arguments
- .model
the model
- .variable
the variable name/definition
- ...
quantifiers for the indexed variable. Including filters
- type
must be either continuous, integer or binary
- lb
the lower bound of the variable
- ub
the upper bound of the variable
- .dots
Used to work around non-standard evaluation.
Examples
library(magrittr)
MIPModel() %>%
add_variable(x) %>% # creates 1 variable named x
add_variable(y[i],
i = 1:10, i %% 2 == 0,
type = "binary"
) # creates 4 variables
#> Mixed integer linear optimization problem
#> Variables:
#> Continuous: 1
#> Integer: 0
#> Binary: 5
#> No objective function.
#> Constraints: 0