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lp.R
# Copyright 2018, Gurobi Optimization, LLC # # This example formulates and solves the following simple LP model: # maximize # x + 2 y + 3 z # subject to # x + y <= 1 # y + z <= 1 library(Matrix) library(gurobi) model <- list() model$A <- matrix(c(1,1,0,0,1,1), nrow=2, byrow=T) model$obj <- c(1,2,3) model$modelsense <- 'max' model$rhs <- c(1,1) model$sense <- c('<', '<') result <- gurobi(model) print(result$objval) print(result$x) # Second option for A - as a sparseMatrix (using the Matrix package)... model$A <- spMatrix(2, 3, c(1, 1, 2, 2), c(1, 2, 2, 3), c(1, 1, 1, 1)) params <- list(Method=2, TimeLimit=100) result <- gurobi(model, params) print(result$objval) print(result$x) # Third option for A - as a sparse triplet matrix (using the slam package)... model$A <- simple_triplet_matrix(c(1, 1, 2, 2), c(1, 2, 2, 3), c(1, 1, 1, 1)) params <- list(Method=2, TimeLimit=100) result <- gurobi(model, params) print(result$objval) print(result$x) # Clear space rm(result, params, model)