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);
}