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## MILP - Example - 1
## min: 3 x + 1 y + 3 z
## s.t.
## -1 x + y + z <= 4
## 4 y - 3 z <= 2
## x - 3 y + 2 z <= 3
## x, z \in Z_+
## y >= 0, z >= 2, x <= 4, y <= 100
test_milp_01 <- function(solver) {
obj <- c(3, 1, 3)
A <- rbind(c(-1, 2, 1),
c( 0, 4, -3),
c( 1, -3, 2))
b <- c(4, 2, 3)
bounds <- V_bound(li = c(1L, 3L), ui = c(1L, 2L),
lb = c(-Inf, 2), ub = c(4, 100))
x <- OP(objective = obj,
constraints = L_constraint(L = A,
dir = c("<=", "<=", "<="),
rhs = b),
types = c("I", "C", "I"),
bounds = bounds,
maximum = TRUE)
sol <- c(4, 2.5, 3)
opt <- ROI_solve(x, solver = solver,
control = solver_control(solver, sol))
check("MILP-01@01", all(A %*% opt$solution - b <= ROI_options("constraint_eps")))
check("MILP-01@02", correct_types(x, solution(opt)))
check("MILP-01@03", check_bounds(x, solution(opt)))
check("MILP-01@04", equal(opt$solution , sol, tol=1e-01))
}
## MILP - Example - 2
## min: 3 x + 1 y + 3 z
## s.t.
## -1 x + y + z <= 4
## 4 y - 3 z <= 2
## x - 3 y + 2 z <= 3
## x, z \in Z_+
## y >= 0
test_milp_02 <- function(solver) {
obj <- c(3, 1, 3)
A <- rbind(c(-1, 2, 1),
c( 0, 4, -3),
c( 1, -3, 2))
b <- c(4, 2, 3)
x <- OP(objective = obj,
constraints = L_constraint(L = A,
dir = c("<=", "<=", "<="),
rhs = b),
types = c("I", "C", "I"),
maximum = TRUE)
sol <- c(5, 2.75, 3)
opt <- ROI_solve(x, solver = solver,
control = solver_control(solver, sol))
check("MILP-02@01", all(A %*% opt$solution - b <= ROI_options("constraint_eps")))
check("MILP-01@02", correct_types(x, solution(opt)))
check("MILP-01@03", check_bounds(x, solution(opt)))
check("MILP-02@04", equal(opt$solution , sol, tol=1e-01))
}
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