# Copyright 2025, 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 modelcat('Reading model',args[1],'...')model<-gurobi_read(args[1])cat('... done\n')# Detect set of non-continous variablesnumvars<-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')}# Optimizeparams<-list()params$poolsolutions<-20result<-gurobi(model,params)# Capture solution informationif(result$status!='OPTIMAL'){cat('Optimization finished with status',result$status,'\n')stop('Stop now\n')}# Iterate over the solutionsif('pool'%in%names(result)){solcount<-length(result$pool)for(kin1:solcount){cat('Solution',k,'has objective:',result$pool[[k]]$objval,'\n')}}else{solcount<-1cat('Solution 1 has objective:',result$objval,'\n')}# Convert to fixed modelfor(jin1:numvars){if(model$vtype[j]!='C'){t<-floor(result$x[j]+0.5)model$lb[j]<-tmodel$ub[j]<-t}}# Solve the fixed modelresult2<-gurobi(model,params)if(result2$status!='OPTIMAL'){stop('Error: fixed model isn\'t optimal\n')}if(abs(result$objval-result2$objval)>1e-6*(1+abs(result$objval))){stop('Error: Objective values differ\n')}# Print values of non-zero variablesfor(jin1:numvars){if(abs(result2$x[j])<1e-6)nextvarnames<-''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 spacerm(model,params,result,result2)