private ResultState SolveInternal() { PrintDebugRessourcesBefore("SolveInternal"); var param = new MPSolverParameters(); param.SetDoubleParam(MPSolverParameters.RELATIVE_MIP_GAP, MIP_GAP); if (timelimit != 0) { solver.SetTimeLimit(timelimit); } #if DEBUG solver.EnableOutput(); #else solver.SuppressOutput(); #endif resultState = FromGoogleResultState(solver.Solve(param)); PrintDebugRessourcesAfter(); #if DEBUG PrintDebugOutput(); #endif return(resultState); }
public override void Solve() { _solutionStatus = Solver.Solve(); }
public static void Run(string inputFile) { Console.WriteLine("Start Knapsack solver..."); //read input string[] inputs = File.ReadAllLines(inputFile); string[] line = inputs[0].Split(' '); int N = Convert.ToInt32(line[0]); // number of objects to pick from int K = Convert.ToInt32(line[1]); // capacity of the sack //create solver // GLOP_LINEAR_PROGRAMMING, CBC_MIXED_INTEGER_PROGRAMMING Google.OrTools.LinearSolver.Solver solver = Google.OrTools.LinearSolver.Solver.CreateSolver("knapsack", "CBC_MIXED_INTEGER_PROGRAMMING"); //objective Objective objective = solver.Objective(); objective.SetMaximization(); //variables Variable[] variables = solver.MakeBoolVarArray(N); //constraints Constraint capacityConstraint = solver.MakeConstraint(0, K); for (int i = 0; i < N; i++) { //get input parameters line = inputs[i + 1].Split(' '); double value = Convert.ToDouble(line[0]); double weight = Convert.ToDouble(line[1]); Variable x = variables[i]; //add to objective objective.SetCoefficient(x, value); //add to constraint capacityConstraint.SetCoefficient(x, weight); } MPSolverParameters solverParams = new MPSolverParameters(); Console.WriteLine("Start solving..."); int resultStatus = solver.Solve(); double resultObjective = 0.0; string resultVariables = ""; Console.WriteLine("Solver finished"); Console.WriteLine("Solution status: " + resultStatus.ToString()); string outputFile = new FileInfo(inputFile).Directory.FullName + @"\output.txt"; if (File.Exists(outputFile)) { File.Delete(outputFile); } if (resultStatus != Google.OrTools.LinearSolver.Solver.OPTIMAL) { resultStatus = 0; Console.WriteLine("The problem don't have an optimal solution."); } else { resultStatus = 1; Console.WriteLine("Solution objective: " + solver.Objective().Value().ToString()); resultObjective = solver.Objective().Value(); foreach (Variable x in variables) { if (resultVariables == "") { resultVariables = x.SolutionValue().ToString(); } else { resultVariables += " " + x.SolutionValue().ToString(); } } Console.WriteLine("Solution variables: " + resultVariables.ToString()); } using (System.IO.StreamWriter file = new System.IO.StreamWriter(outputFile)) { file.WriteLine(resultObjective.ToString() + " " + resultStatus.ToString()); file.WriteLine(resultVariables); } }
public ProblemSolution Solve(ProblemConfiguration config) { var res = new ProblemSolution(); //https://developers.google.com/optimization/mip/mip_var_array#c_1 if (config.AvailableAmount <= 0) { throw new ArgumentException("Invalid configuration - Available amount"); } if (config.Products == null || config.Products.Count == 0) { throw new ArgumentException("Invalid configuration - Products"); } // [START solver] // Create the linear solver with the CBC backend. Solver solver = Solver.CreateSolver(/*"SimpleMipProgram",*/ "CBC"); // [END solver] // [START variables] // x, y and z are integer non-negative variables. var variables = new List <Variable>(); foreach (var p in config.Products) { var variable = solver.MakeIntVar(0.0, double.PositiveInfinity, GetVariableName(p)); variables.Add(variable); if (p.MaxUnits == 0) { solver.Add(variable == 0); } else if ( (p.MinUnits >= 0 && p.MaxUnits > 0 && p.MinUnits < p.MaxUnits) || (p.MaxUnits == p.MinUnits && p.MaxUnits > 0) ) { // other constraints solver.Add(variable >= p.MinUnits); solver.Add(variable <= p.MaxUnits); } } res.TotalVariables = solver.NumVariables(); // [END variables] // [START constraints] // (unitPriceX * x) + (unitPriceY * y) + (unitPriceZ *z) <= maxValue. var c = solver.MakeConstraint(0, config.AvailableAmount); int i = 0; foreach (var variable in variables) { c.SetCoefficient(variable, (double)config.Products[i].UnitPrice); i++; } res.TotalConstraints = solver.NumConstraints(); // [END constraints] Objective objective = solver.Objective(); i = 0; foreach (var variable in variables) { objective.SetCoefficient(variable, (double)config.Products[i].UnitPrice); i++; } objective.SetMaximization(); // [START solve] Solver.ResultStatus resultStatus = solver.Solve(); // [END solve] // [START print_solution] // Check that the problem has an optimal solution. if (resultStatus != Solver.ResultStatus.OPTIMAL) { res.HasOptimalSolution = false; return(res); } res.HasOptimalSolution = true; res.FinalAmount = (decimal)solver.Objective().Value(); res.RemainingAmount = Math.Round(config.AvailableAmount - (double)res.FinalAmount, 2); i = 0; foreach (var variable in variables) { var itemValue = variable.SolutionValue() * (double)config.Products[i].UnitPrice; itemValue = Math.Round(itemValue, 2); res.ResponseVariables.Add( new SolutionVariable() { Name = config.Products[i].Name, //variable.Name(), Code = config.Products[i].Code, SolutionValue = variable.SolutionValue(), UnitPrice = config.Products[i].UnitPrice, FinalAmount = itemValue, Description = variable.Name(), Details = $"{variable.Name()} = {variable.SolutionValue()} /// {variable.SolutionValue()} * {config.Products[i].UnitPrice} = {itemValue} euros " }); i++; } res.SolveTimeMs = solver.WallTime(); res.Iterations = solver.Iterations(); res.Nodes = solver.Nodes(); return(res); }