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mip.R
# Copyright 2021, 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)