# mipSolve: Solve a LP or a MIP In lpmodeler: Modeler for linear programs (LP) and mixed integer linear programs (MILP)

## Description

Solve a linear program (LP) or a mixed integer program (MIP). Find the values of the objective function and the associated variables using the specified solver.

## Usage

 `1` ```mipSolve(p, solver = c("Rsymphony"), ...) ```

## Arguments

 `p` an object of class `lpmodeler` `solver` name of the solver to use: Rsymphony (default) `...` other parameters passed to the solver

## Value

The object returned by the solver

## Author(s)

Cyrille Szymanski <cnszym at gmail.com>

TODO

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22``` ```# create and solve the following linear program: # Simple mixed integer linear program. # max: 3 x1 + 1 x2 + 3 x3 # s.t.: -1 x1 + 2 x2 + x3 <= 4 # 4 x2 - 3 x3 <= 2 # x1 - 3 x2 + 2 x3 <= 3 # x1 >= 0 (integer) # x2 >= 0 (real) # x3 >= 0 (integer) p <- newProblem() p <- addVariable(p, "I", 3) p <- addVariable(p, "C", 1) p <- addVariable(p, "I", 3) p <- addConstraint(p, "<=", 4, c(-1, 2, 1)) p <- addConstraint(p, "<=", 2, c(0, 4, -3)) p <- addConstraint(p, "<=", 3, c(1, -3, 2)) p <- addConstraint(p, ">=", 0, c(1, 0, 0)) p <- addConstraint(p, ">=", 0, c(0, 1, 0)) p <- addConstraint(p, ">=", 0, c(0, 0, 1)) if(require(Rsymphony)) mipSolve(p) ```

### Example output

```Loading required package: Rsymphony

Warning: Trying to use multiple processors with sequential build...
Starting Preprocessing...
Preprocessing finished...
constraints removed: 3

Solving...

****************************************************
* Optimal Solution Found                           *
****************************************************

Solution Found: Node 0, Level 0
Solution Cost: -26.7500000000
\$solution
[1] 5.00 2.75 3.00

\$objval
[1] 26.75

\$status
TM_OPTIMAL_SOLUTION_FOUND
0
```

lpmodeler documentation built on May 2, 2019, 2:46 p.m.