mip.R
# Copyright 2016, Gurobi Optimization, Inc.
#
# This example formulates and solves the following simple MIP model:
# maximize
# x + y + 2 z
# subject to
# x + 2 y + 3 z <= 4
# x + y >= 1
# x, y, z binary
library("gurobi")
model <- list()
model$A <- matrix(c(1,2,3,1,1,0), nrow=2, ncol=3, byrow=T)
model$obj <- c(1,1,2)
model$modelsense <- "max"
model$rhs <- c(4,1)
model$sense <- c('<=', '>=')
model$vtype <- 'B'
params <- list(OutputFlag=0)
result <- gurobi(model, params)
print('Solution:')
print(result$objval)
print(result$x)
