intlinprog: MatLab(R)-style Mixed Integer Linear Programming in R using...
In modopt.matlab: 'MatLab'-Style Modeling of Optimization Problems

Description Usage Arguments Value Author(s) Examples

intlinprog provides a simple interface to ROI using the optimization model specification of MatLab(R)

minimize in x: f'*x subject to A*x <= b Aeq*x == beq x >= lb x <= ub

1 2	intlinprog(f, intcon = NULL, A = NULL, b = NULL, Aeq = NULL, beq = NULL, lb = NULL, ub = NULL, x0 = NULL, options = NULL)

`f`	Linear term (vector) of the objective function
`intcon`	Vector of which variables are integer
`A`	Inequality constraints (left-hand side)
`b`	Inequality constraints (right-hand side)
`Aeq`	Equality constraints (left-hand side)
`beq`	Equality constraints (right-hand side)
`lb`	Lower bound
`ub`	Upper bound
`x0`	Initial solution
`options`	Additional optimization parameters

The solution vector in x as well as the objective value in fval.

Ronald Hochreiter, ron@hochreiter.net

# minimize 8x1 + x2
# subject to
#   x1 + 2x2 >= -14
#   -4x1 - 1x2 <= -33
#   2x1 + x2 <= 20
#   x1, x2 integer

f <- c(8, 1)
A <- matrix(c(-1, -2, -4, -1, 2, 1), nrow=3, byrow=TRUE)
b <- c(14, -33, 20)

sol <- intlinprog(f, c(1, 2), A, b)
sol <- intlinprog(f, NULL, A, b)

sol$x