Try our new documentation site (beta).


mip2.R


# Copyright 2020, Gurobi Optimization, LLC
#
# This example reads a MIP model from a file, solves it and
# prints the objective values from all feasible solutions
# generated while solving the MIP. Then it creates the fixed
# model and solves that model.

library(Matrix)
library(gurobi)

args <- commandArgs(trailingOnly = TRUE)
if (length(args) < 1) {
  stop('Usage: Rscript mip2.R filename\n')
}

# Read model
cat('Reading model',args[1],'...')
model <- gurobi_read(args[1])
cat('... done\n')

# Detect set of non-continous variables
numvars    <- dim(model$A)[[2]]
intvars    <- which(model$vtype != 'C')
numintvars <- length(intvars)
if (numintvars < 1) {
  stop('All model\'s variables are continuous, nothing to do\n')
}

# Optimize
params               <- list()
params$poolsolutions <- 20
result               <- gurobi(model, params)

# Capture solution information
if (result$status != 'OPTIMAL') {
  cat('Optimization finished with status', result$status, '\n')
  stop('Stop now\n')
}

# Iterate over the solutions
if ('pool' %in% names(result)) {
  solcount <- length(result$pool)
  for (k in 1:solcount) {
    cat('Solution', k, 'has objective:', result$pool[[k]]$objval, '\n')
  }
} else {
  solcount <- 1
  cat('Solution 1 has objective:', result$objval, '\n')
}

# Convert to fixed model
for (j in 1:numvars) {
  if (model$vtype[j] != 'C') {
    t <- floor(result$x[j]+0.5)
    model$lb[j] <- t
    model$ub[j] <- t
  }
}

# Solve the fixed model
result2 <- gurobi(model, params)
if (result2$status != 'OPTIMAL') {
  stop('Error: fixed model isn\'t optimal\n')
}

if (abs(result$objval - result2$objval) > 1e-6 * (1 + abs(result$objval))) {
  stop('Error: Objective values differ\n')
}

# Print values of non-zero variables
for (j in 1:numvars) {
  if (abs(result2$x[j]) < 1e-6) next
  varnames <- ''
  if ('varnames' %in% names(model)) {
    varnames <- model$varnames[j]
  } else {
    varnames <- sprintf('X%d', j)
  }
  cat(format(varnames, justify='left', width=10),':',
      format(result2$x[j], justify='right', digits=2, width=10), '\n')
}

# Clear space
rm(model, params, result, result2)

Try Gurobi for Free

Choose the evaluation license that fits you best, and start working with our Expert Team for technical guidance and support.

Evaluation License
Get a free, full-featured license of the Gurobi Optimizer to experience the performance, support, benchmarking and tuning services we provide as part of our product offering.
Academic License
Gurobi supports the teaching and use of optimization within academic institutions. We offer free, full-featured copies of Gurobi for use in class, and for research.
Cloud Trial

Request free trial hours, so you can see how quickly and easily a model can be solved on the cloud.

Search

Gurobi Optimization