private void AddTargetFunction()
{
PrintDebugRessourcesBefore("AddTargetFunction");
var factory = new TargetFunctionFactory(solverData);
var targetFunction = new GLS.LinearExpr();
targetFunction += factory.CreateTargetFunction(TargetType.MinTime, WaytimeWeight);
targetFunction += factory.CreateTargetFunction(TargetType.TryVisitDesired, DesiredWeight);
solverData.Solver.Minimize(targetFunction);
// constraint target function based on presolved solution
if (solverData.Input.Presolved.Length > 0)
{
var totalTimePresolved = 0;
for (int i = 1; i < solverData.Input.Presolved.Length; i++)
{
totalTimePresolved += solverData.Input.VisitsDuration[Array.IndexOf(solverData.Input.VisitIds, solverData.Input.Presolved[i] - 1)];
totalTimePresolved += solverData.Input.Distances[i > 1 ? Array.IndexOf(solverData.Input.VisitIds, solverData.Input.Presolved[i - 1] - 1) : 0, Array.IndexOf(solverData.Input.VisitIds, solverData.Input.Presolved[i] - 1)];
}
totalTimePresolved += solverData.Input.Distances[Array.IndexOf(solverData.Input.VisitIds, solverData.Input.Presolved.Last() - 1), 0];
solver.Add(targetFunction <= totalTimePresolved * WaytimeWeight);
}
var minWayTime = solverData.Input.Distances.Cast <int>().Where(i => i > 0).Min();
solver.Add(targetFunction >= (minWayTime * (solverData.NumberOfVisits + 1) + solverData.Input.VisitsDuration.Sum()) * (WaytimeWeight - DesiredWeight));
PrintDebugRessourcesAfter();
}
/**
*
* Volsay problem.
*
* From the OPL model volsay.mod.
*
*
* Also see http://www.hakank.org/or-tools/volsay.py
*
*/
private static void Solve()
{
Solver solver = new Solver("Volsay", Solver.CLP_LINEAR_PROGRAMMING);
//
// Variables
//
Variable Gas = solver.MakeNumVar(0, 100000, "Gas");
Variable Chloride = solver.MakeNumVar(0, 100000, "Cloride");
Constraint c1 = solver.Add(Gas + Chloride <= 50);
Constraint c2 = solver.Add(3 * Gas + 4 * Chloride <= 180);
solver.Maximize(40 * Gas + 50 * Chloride);
int resultStatus = solver.Solve();
if (resultStatus != Solver.OPTIMAL) {
Console.WriteLine("The problem don't have an optimal solution.");
return;
}
Console.WriteLine("Objective: {0}", solver.ObjectiveValue());
Console.WriteLine("Gas : {0} ReducedCost: {1}",
Gas.SolutionValue(),
Gas.ReducedCost());
Console.WriteLine("Chloride : {0} ReducedCost: {1}",
Chloride.SolutionValue(),
Chloride.ReducedCost());
Console.WriteLine("c1 : DualValue: {0} Activity: {1}",
c1.DualValue(),
c1.Activity());
Console.WriteLine("c2 : DualValue: {0} Activity: {1}",
c2.DualValue(),
c2.Activity());
Console.WriteLine("\nWallTime: " + solver.WallTime());
Console.WriteLine("Iterations: " + solver.Iterations());
}
private void AddTargetFunction()
{
PrintDebugRessourcesBefore("AddTargetFunction");
var targetFunction = new LinearExpr();
var hour = 3600;
var santaWorkingTime = new LinearExpr[solverData.NumberOfSantas];
var longestDay = solver.MakeIntVar(0, int.MaxValue, "longest day");
foreach (var santa in Enumerable.Range(0, solverData.NumberOfSantas))
{
santaWorkingTime[santa] = solverData.Variables.SantaVisitTime[santa] + solverData.Variables.SantaRouteCost[santa];
solver.Add(longestDay >= santaWorkingTime[santa]);
}
var workingTimeFactor = (40d / hour);
var longestDayFactor = (30d / hour);
targetFunction = workingTimeFactor * santaWorkingTime.Sum()
+ longestDayFactor * longestDay;
solverData.Solver.Minimize(targetFunction);
PrintDebugRessourcesAfter();
}
static void TestVarAddition()
{
Console.WriteLine("Running TestVarAddition");
Solver solver = new Solver("TestVarAddition",
Solver.CLP_LINEAR_PROGRAMMING);
Variable x = solver.MakeNumVar(0.0, 100.0, "x");
Variable y = solver.MakeNumVar(0.0, 100.0, "y");
Constraint ct1 = solver.Add(x + y == 1);
CheckDoubleEq(ct1.GetCoefficient(x), 1.0, "test1");
CheckDoubleEq(ct1.GetCoefficient(y), 1.0, "test2");
Constraint ct2 = solver.Add(x + x == 1);
CheckDoubleEq(ct2.GetCoefficient(x), 2.0, "test3");
Constraint ct3 = solver.Add(x + (y + x) == 1);
CheckDoubleEq(ct3.GetCoefficient(x), 2.0, "test4");
CheckDoubleEq(ct3.GetCoefficient(y), 1.0, "test5");
Constraint ct4 = solver.Add(x + (y + x + 3) == 1);
CheckDoubleEq(ct4.GetCoefficient(x), 2.0, "test4");
CheckDoubleEq(ct4.GetCoefficient(y), 1.0, "test5");
CheckDoubleEq(ct4.Lb(), -2.0, "test6");
CheckDoubleEq(ct4.Ub(), -2.0, "test7");
}
static void TestVarOperator()
{
Console.WriteLine("Running TestVarOperator");
Solver solver = new Solver("TestVarOperator",
Solver.CLP_LINEAR_PROGRAMMING);
Variable x = solver.MakeNumVar(0.0, 100.0, "x");
Constraint ct1 = solver.Add(x >= 1);
Constraint ct2 = solver.Add(x <= 1);
Constraint ct3 = solver.Add(x == 1);
Constraint ct4 = solver.Add(1 >= x);
Constraint ct5 = solver.Add(1 <= x);
Constraint ct6 = solver.Add(1 == x);
CheckDoubleEq(ct1.GetCoefficient(x), 1.0, "test1");
CheckDoubleEq(ct2.GetCoefficient(x), 1.0, "test2");
CheckDoubleEq(ct3.GetCoefficient(x), 1.0, "test3");
CheckDoubleEq(ct4.GetCoefficient(x), 1.0, "test4");
CheckDoubleEq(ct5.GetCoefficient(x), 1.0, "test5");
CheckDoubleEq(ct6.GetCoefficient(x), 1.0, "test6");
CheckDoubleEq(ct1.Lb(), 1.0, "test7");
CheckDoubleEq(ct1.Ub(), double.PositiveInfinity, "test8");
CheckDoubleEq(ct2.Lb(), double.NegativeInfinity, "test9");
CheckDoubleEq(ct2.Ub(), 1.0, "test10");
CheckDoubleEq(ct3.Lb(), 1.0, "test11");
CheckDoubleEq(ct3.Ub(), 1.0, "test12");
CheckDoubleEq(ct4.Lb(), double.NegativeInfinity, "test13");
CheckDoubleEq(ct4.Ub(), 1.0, "test14");
CheckDoubleEq(ct5.Lb(), 1.0, "test15");
CheckDoubleEq(ct5.Ub(), double.PositiveInfinity, "test16");
CheckDoubleEq(ct6.Lb(), 1.0, "test17");
CheckDoubleEq(ct6.Ub(), 1.0, "test18");
}
/**
*
* Volsay problem.
*
* From the OPL model volsay.mod.
* This version use arrays and matrices
*
*
* Also see
* http://www.hakank.org/or-tools/volsay2.cs
* http://www.hakank.org/or-tools/volsay3.py
*
*/
private static void Solve()
{
Solver solver = new Solver("Volsay3",
Solver.CLP_LINEAR_PROGRAMMING);
int num_products = 2;
IEnumerable<int> PRODUCTS = Enumerable.Range(0, num_products);
String[] products = {"Gas", "Chloride"};
String[] components = {"nitrogen", "hydrogen", "chlorine"};
int[,] demand = { {1,3,0}, {1,4,1}};
int[] profit = {30,40};
int[] stock = {50,180,40};
//
// Variables
//
Variable[] production = new Variable[num_products];
foreach(int p in PRODUCTS) {
production[p] = solver.MakeNumVar(0, 100000, products[p]);
}
//
// Constraints
//
int c_len = components.Length;
Constraint[] cons = new Constraint[c_len];
for(int c = 0; c < c_len; c++) {
cons[c] = solver.Add( (from p in PRODUCTS
select (demand[p,c]*production[p])).
ToArray().Sum() <= stock[c]);
}
//
// Objective
//
solver.Maximize( (from p in PRODUCTS
select (profit[p]*production[p])).
ToArray().Sum()
);
if (solver.Solve() != Solver.OPTIMAL) {
Console.WriteLine("The problem don't have an optimal solution.");
return;
}
Console.WriteLine("Objective: {0}", solver.ObjectiveValue());
foreach(int p in PRODUCTS) {
Console.WriteLine("{0,-10}: {1} ReducedCost: {2}",
products[p],
production[p].SolutionValue(),
production[p].ReducedCost());
}
for(int c = 0; c < c_len; c++) {
Console.WriteLine("Constraint {0} DualValue {1} Activity: {2} lb: {3} ub: {4}",
c,
cons[c].DualValue(),
cons[c].Activity(),
cons[c].Lb(),
cons[c].Ub());
}
Console.WriteLine("\nWallTime: " + solver.WallTime());
Console.WriteLine("Iterations: " + solver.Iterations());
}
static void TestVarMultiplication()
{
Console.WriteLine("Running TestVarMultiplication");
Solver solver = new Solver("TestVarMultiplication",
Solver.CLP_LINEAR_PROGRAMMING);
Variable x = solver.MakeNumVar(0.0, 100.0, "x");
Variable y = solver.MakeNumVar(0.0, 100.0, "y");
Constraint ct1 = solver.Add(3 * x == 1);
CheckDoubleEq(ct1.GetCoefficient(x), 3.0, "test1");
Constraint ct2 = solver.Add(x * 3 == 1);
CheckDoubleEq(ct2.GetCoefficient(x), 3.0, "test2");
Constraint ct3 = solver.Add(x + (2 * y + 3 * x) == 1);
CheckDoubleEq(ct3.GetCoefficient(x), 4.0, "test3");
CheckDoubleEq(ct3.GetCoefficient(y), 2.0, "test4");
Constraint ct4 = solver.Add(x + 5 * (y + x + 3) == 1);
CheckDoubleEq(ct4.GetCoefficient(x), 6.0, "test5");
CheckDoubleEq(ct4.GetCoefficient(y), 5.0, "test6");
CheckDoubleEq(ct4.Lb(), -14.0, "test7");
CheckDoubleEq(ct4.Ub(), -14.0, "test8");
Constraint ct5 = solver.Add(x + (2 * y + x + 3) * 3 == 1);
CheckDoubleEq(ct5.GetCoefficient(x), 4.0, "test9");
CheckDoubleEq(ct5.GetCoefficient(y), 6.0, "test10");
CheckDoubleEq(ct5.Lb(), -8.0, "test11");
CheckDoubleEq(ct5.Ub(), -8.0, "test12");
}
static void TestSumArray()
{
Console.WriteLine("Running TestSumArray");
Solver solver = new Solver("TestSumArray", Solver.CLP_LINEAR_PROGRAMMING);
Variable[] x = solver.MakeBoolVarArray(10, "x");
Constraint ct1 = solver.Add(x.Sum() == 3);
CheckDoubleEq(ct1.GetCoefficient(x[0]), 1.0, "test1");
Constraint ct2 = solver.Add(-2 * x.Sum() == 3);
CheckDoubleEq(ct2.GetCoefficient(x[0]), -2.0, "test2");
LinearExpr[] array = new LinearExpr[] { x[0]+ 2.0, x[0] + 3, x[0] + 4 };
Constraint ct3 = solver.Add(array.Sum() == 1);
CheckDoubleEq(ct3.GetCoefficient(x[0]), 3.0, "test3");
CheckDoubleEq(ct3.Lb(), -8.0, "test4");
CheckDoubleEq(ct3.Ub(), -8.0, "test5");
}
static void TestInequalities()
{
Console.WriteLine("Running TestInequalities");
Solver solver = new Solver("TestInequalities",
Solver.CLP_LINEAR_PROGRAMMING);
Variable x = solver.MakeNumVar(0.0, 100.0, "x");
Variable y = solver.MakeNumVar(0.0, 100.0, "y");
Constraint ct1 = solver.Add(2 * (x + 3) + 5 * (y + x -1) >= 3);
CheckDoubleEq(ct1.GetCoefficient(x), 7.0, "test1");
CheckDoubleEq(ct1.GetCoefficient(y), 5.0, "test2");
CheckDoubleEq(ct1.Lb(), 2.0, "test3");
CheckDoubleEq(ct1.Ub(), double.PositiveInfinity, "test4");
Constraint ct2 = solver.Add(2 * (x + 3) + 5 * (y + x -1) <= 3);
CheckDoubleEq(ct2.GetCoefficient(x), 7.0, "test5");
CheckDoubleEq(ct2.GetCoefficient(y), 5.0, "test6");
CheckDoubleEq(ct2.Lb(), double.NegativeInfinity, "test7");
CheckDoubleEq(ct2.Ub(), 2.0, "test8");
Constraint ct3 = solver.Add(2 * (x + 3) + 5 * (y + x -1) >= 3 - x - y);
CheckDoubleEq(ct3.GetCoefficient(x), 8.0, "test9");
CheckDoubleEq(ct3.GetCoefficient(y), 6.0, "test10");
CheckDoubleEq(ct3.Lb(), 2.0, "test11");
CheckDoubleEq(ct3.Ub(), double.PositiveInfinity, "test12");
Constraint ct4 = solver.Add(2 * (x + 3) + 5 * (y + x -1) <= -x - y + 3);
CheckDoubleEq(ct4.GetCoefficient(x), 8.0, "test13");
CheckDoubleEq(ct4.GetCoefficient(y), 6.0, "test14");
CheckDoubleEq(ct4.Lb(), double.NegativeInfinity, "test15");
CheckDoubleEq(ct4.Ub(), 2.0, "test16");
}
static void TestBinaryOperations()
{
Console.WriteLine("Running TestBinaryOperations");
Solver solver = new Solver("TestBinaryOperations",
Solver.CLP_LINEAR_PROGRAMMING);
Variable x = solver.MakeNumVar(0.0, 100.0, "x");
Variable y = solver.MakeNumVar(0.0, 100.0, "y");
Constraint ct1 = solver.Add(x == y);
CheckDoubleEq(ct1.GetCoefficient(x), 1.0, "test1");
CheckDoubleEq(ct1.GetCoefficient(y), -1.0, "test2");
Constraint ct2 = solver.Add(x == 3 * y + 5);
CheckDoubleEq(ct2.GetCoefficient(x), 1.0, "test3");
CheckDoubleEq(ct2.GetCoefficient(y), -3.0, "test4");
CheckDoubleEq(ct2.Lb(), 5.0, "test5");
CheckDoubleEq(ct2.Ub(), 5.0, "test6");
Constraint ct3 = solver.Add(2 * x - 9 == y);
CheckDoubleEq(ct3.GetCoefficient(x), 2.0, "test7");
CheckDoubleEq(ct3.GetCoefficient(y), -1.0, "test8");
CheckDoubleEq(ct3.Lb(), 9.0, "test9");
CheckDoubleEq(ct3.Ub(), 9.0, "test10");
Check(x == x, "test11");
Check(!(x == y), "test12");
Check(!(x != x), "test13");
Check((x != y), "test14");
}
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);
}
/**
*
* Volsay problem.
*
* From the OPL model volsay.mod.
*
*
*
* Also see
* http://www.hakank.org/or-tools/volsay.cs
* http://www.hakank.org/or-tools/volsay2.py
*
*/
private static void Solve()
{
Solver solver = new Solver("Volsay2",
Solver.CLP_LINEAR_PROGRAMMING);
int num_products = 2;
IEnumerable<int> PRODUCTS = Enumerable.Range(0, num_products);
int Gas = 0;
int Chloride = 1;
String[] products = {"Gas", "Chloride"};
//
// Variables
//
Variable[] production = new Variable[num_products];
foreach(int p in PRODUCTS) {
production[p] = solver.MakeNumVar(0, 100000, products[p]);
}
int num_constraints = 2;
IEnumerable<int> CONSTRAINTS = Enumerable.Range(0, num_constraints);
Constraint[] cons = new Constraint[num_constraints];
cons[0] = solver.Add(production[Gas] + production[Chloride] <= 50);
cons[1] = solver.Add(3 * production[Gas] + 4 * production[Chloride] <= 180);
solver.Maximize(40 * production[Gas] + 50 * production[Chloride]);
Console.WriteLine("NumConstraints: {0}", solver.NumConstraints());
int resultStatus = solver.Solve();
if (resultStatus != Solver.OPTIMAL) {
Console.WriteLine("The problem don't have an optimal solution.");
return;
}
foreach(int p in PRODUCTS) {
Console.WriteLine("{0,-10}: {1} ReducedCost: {2}",
products[p],
production[p].SolutionValue(),
production[p].ReducedCost());
}
foreach(int c in CONSTRAINTS) {
Console.WriteLine("Constraint {0} DualValue {1} Activity: {2} lb: {3} ub: {4}",
c.ToString(),
cons[c].DualValue(),
cons[c].Activity(),
cons[c].Lb(),
cons[c].Ub()
);
}
Console.WriteLine("\nWallTime: " + solver.WallTime());
Console.WriteLine("Iterations: " + solver.Iterations());
}