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diet_cs.cs
/* Copyright 2024, Gurobi Optimization, LLC */ /* Solve the classic diet model, showing how to add constraints to an existing model. */ using System; using Gurobi; class diet_cs { static void Main() { try { // Nutrition guidelines, based on // USDA Dietary Guidelines for Americans, 2005 // http://www.health.gov/DietaryGuidelines/dga2005/ string[] Categories = new string[] { "calories", "protein", "fat", "sodium" }; int nCategories = Categories.Length; double[] minNutrition = new double[] { 1800, 91, 0, 0 }; double[] maxNutrition = new double[] { 2200, GRB.INFINITY, 65, 1779 }; // Set of foods string[] Foods = new string[] { "hamburger", "chicken", "hot dog", "fries", "macaroni", "pizza", "salad", "milk", "ice cream" }; int nFoods = Foods.Length; double[] cost = new double[] { 2.49, 2.89, 1.50, 1.89, 2.09, 1.99, 2.49, 0.89, 1.59 }; // Nutrition values for the foods double[,] nutritionValues = new double[,] { { 410, 24, 26, 730 }, // hamburger { 420, 32, 10, 1190 }, // chicken { 560, 20, 32, 1800 }, // hot dog { 380, 4, 19, 270 }, // fries { 320, 12, 10, 930 }, // macaroni { 320, 15, 12, 820 }, // pizza { 320, 31, 12, 1230 }, // salad { 100, 8, 2.5, 125 }, // milk { 330, 8, 10, 180 } // ice cream }; // Model GRBEnv env = new GRBEnv(); GRBModel model = new GRBModel(env); model.ModelName = "diet"; // Create decision variables for the nutrition information, // which we limit via bounds GRBVar[] nutrition = new GRBVar[nCategories]; for (int i = 0; i < nCategories; ++i) { nutrition[i] = model.AddVar(minNutrition[i], maxNutrition[i], 0, GRB.CONTINUOUS, Categories[i]); } // Create decision variables for the foods to buy // // Note: For each decision variable we add the objective coefficient // with the creation of the variable. GRBVar[] buy = new GRBVar[nFoods]; for (int j = 0; j < nFoods; ++j) { buy[j] = model.AddVar(0, GRB.INFINITY, cost[j], GRB.CONTINUOUS, Foods[j]); } // The objective is to minimize the costs // // Note: The objective coefficients are set during the creation of // the decision variables above. model.ModelSense = GRB.MINIMIZE; // Nutrition constraints for (int i = 0; i < nCategories; ++i) { GRBLinExpr ntot = 0.0; for (int j = 0; j < nFoods; ++j) ntot.AddTerm(nutritionValues[j,i], buy[j]); model.AddConstr(ntot == nutrition[i], Categories[i]); } // Solve model.Optimize(); PrintSolution(model, buy, nutrition); Console.WriteLine("\nAdding constraint: at most 6 servings of dairy"); model.AddConstr(buy[7] + buy[8] <= 6.0, "limit_dairy"); // Solve model.Optimize(); PrintSolution(model, buy, nutrition); // Dispose of model and env model.Dispose(); env.Dispose(); } catch (GRBException e) { Console.WriteLine("Error code: " + e.ErrorCode + ". " + e.Message); } } private static void PrintSolution(GRBModel model, GRBVar[] buy, GRBVar[] nutrition) { if (model.Status == GRB.Status.OPTIMAL) { Console.WriteLine("\nCost: " + model.ObjVal); Console.WriteLine("\nBuy:"); for (int j = 0; j < buy.Length; ++j) { if (buy[j].X > 0.0001) { Console.WriteLine(buy[j].VarName + " " + buy[j].X); } } Console.WriteLine("\nNutrition:"); for (int i = 0; i < nutrition.Length; ++i) { Console.WriteLine(nutrition[i].VarName + " " + nutrition[i].X); } } else { Console.WriteLine("No solution"); } } }