Package 'ROI.plugin.msbinlp'

Multiple Solutions - Binary LP

Description

$maximize \ \ x + y$

$subject \ to \ \ x + y = 1$

$x, y \in \{0, 1\}$

Examples

## Not run: 
library(ROI)
op <- OP(objective = c(1, 1),
         constraints = L_constraint(c(1, 1), "==", 1),
         types = c("B", "B"))

x <- ROI_solve(op, solver = "msbinlp", method = "glpk", nsol_max = 2L)
x
## 2 optimal solutions found.
## The objective value is: 1.000000e+00
solution(x)
## [[1]]
## [1] 1 0
##
## [[2]]
## [1] 0 1

## End(Not run)

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Multiple Solutions - Binary LP

Description

$maximize \ \ - x_1 - x_2 - x_3 - x_4 - 99 x_5$

$subject \ to$

$x_1 + x_2 \leq 1$

$x_3 + x_4 \leq 1$

$x_4 + x_5 \leq 1$

$x_i \in \{0, 1\}$

References

Matteo Fischetti and Domenico Salvagnin (2010) Pruning moves. INFORMS Journal on Computing 22.1: 108-119.

Examples

## Not run: 
library(ROI)
op <- OP()
objective(op) <- L_objective(c(-1, -1, -1, -1, -99))
mat <- simple_triplet_matrix(rep(1:3, 2), 
                             c(c(1, 3, 4), c(2, 4, 5)), 
                             rep(1, 6))
constraints(op) <- L_constraint(mat, 
                               dir = leq(3), 
                               rhs = rep.int(1, 3))
types(op) <- rep("B", length(op))

x <- ROI_solve(op, solver = "msbinlp", method = "glpk", nsol_max = 2L)
x 
## 2 optimal solutions found.
## The objective value is: -1.010000e+02
solution(x)
## [[1]]
## [1] 0 1 1 0 1
## 
## [[2]]
## [1] 1 0 1 0 1

## End(Not run)

---