mip.R#

# Copyright 2024, Gurobi Optimization, LLC
#
# 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)

# Clear space
rm(model, result, params)