private void BuildConst()
{
//GRBLinExpr myExpr = 0;
//foreach (Node n in Frmk.Data.NodeSet)
//{
// myExpr += _model.GetVarByName("x_" + n.ID);
//}
//_model.AddConstr(myExpr >= 9, "custom");
foreach (LazyConstr constr in Frmk.ConstrPool)
{
GRBLinExpr expr = 0;
foreach (Node n in constr.Alpha.Keys)
{
expr += (-Frmk.Data.M * constr.Alpha[n]) * _model.GetVarByName("x_" + n.ID);
}
foreach (Node n in constr.Beta.Keys)
{
expr += n.Demand * constr.Beta[n];
}
foreach (Arc a in constr.Gamma.Keys)
{
expr += (-a.Capacity) * constr.Gamma[a];
}
if (constr.Type == "OPTIMAL")
{
_model.AddConstr(expr <= _model.GetVarByName("z"), "ct_o_" + constr.ID);
}
else if (constr.Type == "FEASIBLE")
{
_model.AddConstr(expr <= 0, "ct_f_" + constr.ID);
}
}
}
private void BuildMIPModel()
{
_env = new GRBEnv();
_model = new GRBModel(_env);
//room used.
varR = new Dictionary <Room, GRBVar>();
foreach (var room in Data.Rooms)
{
varR[room] = _model.AddVar(0, GRB.INFINITY, room.Cost, GRB.INTEGER,
$"r_{room}");
}
_model.Update();
_model.AddConstr(Data.TimeSlots.Count * varR.Values.Sumx(), GRB.GREATER_EQUAL, Data.Courses.Sum(c => c.Lectures), "");
foreach (var roomCapacity in Data.RoomCapacities)
{
var overCap = OverCapacity * ((double)Data.Courses.Where(c => c.NumberOfStudents > roomCapacity.Value).Sum(c => c.Lectures) / Data.TimeSlots.Count);
_model.AddConstr(varR.Where(r => r.Key.Capacity > roomCapacity.Value).Sumx(r => r.Value) * Data.TimeSlots.Count, GRB.GREATER_EQUAL,
Data.Courses.Where(c => c.NumberOfStudents > roomCapacity.Value).Sum(c => c.Lectures) + overCap,
$"roomcapcut_{roomCapacity.Value}");
}
_model.SetCallback(new OutputCallback());
}
static void Main(string[] args)
{
GRBEnv env = new GRBEnv();
GRBModel m = new GRBModel(env);
GRBVar x1 = m.AddVar(0, GRB.INFINITY, 20, GRB.CONTINUOUS, "food.1");
GRBVar x2 = m.AddVar(0, GRB.INFINITY, 10, GRB.CONTINUOUS, "food.2");
GRBVar x3 = m.AddVar(0, GRB.INFINITY, 31, GRB.CONTINUOUS, "food.3");
GRBVar x4 = m.AddVar(0, GRB.INFINITY, 11, GRB.CONTINUOUS, "food.4");
GRBVar x5 = m.AddVar(0, GRB.INFINITY, 12, GRB.CONTINUOUS, "food.5");
m.Update();
GRBConstr con1 = m.AddConstr(2 * x1 + 3 * x3 + 1 * x4 + 2 * x5 >= 21, "nutrient.iron");
GRBConstr con2 = m.AddConstr(1 * x2 + 2 * x3 + 2 * x4 + 1 * x5 >= 12, "nutrient.calcium");
m.Optimize();
m.Write("diet.lp");
foreach (GRBVar var in m.GetVars())
{
Console.WriteLine("{0} = {1}, reduced cost = {2}", var.Get(GRB.StringAttr.VarName), var.Get(GRB.DoubleAttr.X), var.Get(GRB.DoubleAttr.RC));
}
foreach (GRBConstr constr in m.GetConstrs())
{
Console.WriteLine("{0}, slack = {1}, pi = {2}", constr.Get(GRB.StringAttr.ConstrName), constr.Get(GRB.DoubleAttr.Slack), constr.Get(GRB.DoubleAttr.Pi));
}
m.Dispose();
env.Dispose();
}
static void Main()
{
try {
GRBEnv env = new GRBEnv("qp.log");
GRBModel model = new GRBModel(env);
// Create variables
GRBVar x = model.AddVar(0.0, 1.0, 0.0, GRB.CONTINUOUS, "x");
GRBVar y = model.AddVar(0.0, 1.0, 0.0, GRB.CONTINUOUS, "y");
GRBVar z = model.AddVar(0.0, 1.0, 0.0, GRB.CONTINUOUS, "z");
// Set objective
GRBQuadExpr obj = x * x + x * y + y * y + y * z + z * z + 2 * x;
model.SetObjective(obj);
// Add constraint: x + 2 y + 3 z >= 4
model.AddConstr(x + 2 * y + 3 * z >= 4.0, "c0");
// Add constraint: x + y >= 1
model.AddConstr(x + y >= 1.0, "c1");
// Optimize model
model.Optimize();
Console.WriteLine(x.VarName + " " + x.X);
Console.WriteLine(y.VarName + " " + y.X);
Console.WriteLine(z.VarName + " " + z.X);
Console.WriteLine("Obj: " + model.ObjVal + " " + obj.Value);
// Change variable types to integer
x.VType = GRB.INTEGER;
y.VType = GRB.INTEGER;
z.VType = GRB.INTEGER;
// Optimize model
model.Optimize();
Console.WriteLine(x.VarName + " " + x.X);
Console.WriteLine(y.VarName + " " + y.X);
Console.WriteLine(z.VarName + " " + z.X);
Console.WriteLine("Obj: " + model.ObjVal + " " + obj.Value);
// Dispose of model and env
model.Dispose();
env.Dispose();
} catch (GRBException e) {
Console.WriteLine("Error code: " + e.ErrorCode + ". " + e.Message);
}
}
private void GenerateConst()
{
GRBLinExpr expr1 = 0;
foreach (Scheme s in SchemeColumnPool)
{
expr1 += _grbModelMaster.GetVarByName("lambda_" + s.ID);
}
_grbModelMaster.AddConstr(expr1 == 1, "ct1");
GRBLinExpr expr2 = 0;
foreach (ExtremePoint e in EPColumnPool)
{
expr2 += _grbModelMaster.GetVarByName("mu_" + e.ID);
}
_grbModelMaster.AddConstr(expr2 == 1, "ct2");
foreach (Node n in Data.NodeSet)
{
GRBLinExpr expr = 0;
foreach (Scheme s in SchemeColumnPool)
{
GRBVar lambda = _grbModelMaster.GetVarByName("lambda_" + s.ID);
expr += Data.ServerCapacity * s.Value[n] * lambda;
}
foreach (ExtremePoint e in EPColumnPool)
{
GRBVar mu = _grbModelMaster.GetVarByName("mu_" + e.ID);
expr += -e.Value[n] * mu;
}
_grbModelMaster.AddConstr(expr >= 0, "ct3_" + n.ID);
}
}
internal void AddCalculationTime(double calculationSeconds)
{
var calculationVar = _model.AddVar(0, double.PositiveInfinity, 0, GRB.CONTINUOUS, "calculationTime");
_model.AddConstr(calculationSeconds == calculationVar, "calculationTimeConstraint");
_variables[(int)VariableTypes.CalculationTime] = calculationVar;
}
private void BuildFlowBalanceConst()
{
foreach (Node n in Data.NodeSet)
{
GRBLinExpr exprLeft = 0;
foreach (Arc a in Data.ArcSet)
{
if (a.FromNode == n)
{
GRBVar x = _grbModel_FlowAssignmentSub.GetVarByName("x_" + a.FromNode.ID + "_" + a.ToNode.ID);
exprLeft += x;
}
}
exprLeft += n.Demand;
GRBLinExpr exprRight = 0;
foreach (Arc a in Data.ArcSet)
{
if (a.ToNode == n)
{
GRBVar x = _grbModel_FlowAssignmentSub.GetVarByName("x_" + a.FromNode.ID + "_" + a.ToNode.ID);
exprRight += x;
}
}
exprRight += _grbModel_FlowAssignmentSub.GetVarByName("g_" + n.ID);
_grbModel_FlowAssignmentSub.AddConstr(exprLeft == exprRight, "ct_FlBal_" + n.ID);
}
}
private void IncomingOutgoingWaysConstraints(GRBModel model, int numberOfRoutes, GRBVar[][] w, GRBVar[][] v)
{
for (int i = 1; i < distances.GetLength(0); i++)
{
if (input.Visits[i - 1].IsBreak)
{
continue;
}
var wki = new GRBLinExpr(0);
var wik = new GRBLinExpr(0);
for (int s = 0; s < numberOfRoutes; s++)
{
for (int k = 0; k < distances.GetLength(1); k++)
{
var swki = AccessW(w[s], k, i);
var swik = AccessW(w[s], i, k);
wki += swki;
wik += swik;
}
}
model.AddConstr(wki == 1, $"v{i} incoming ways == 1");
model.AddConstr(wik == 1, $"v{i} outgoing ways == 1");
}
}
private void AddTargetFunction()
{
PrintDebugRessourcesBefore("AddTargetFunction");
var factory = new TargetFunctionFactory(solverData);
var targetFunction = new GRBLinExpr(0);
targetFunction += factory.CreateTargetFunction(TargetType.MinTime, WaytimeWeight);
targetFunction += factory.CreateTargetFunction(TargetType.TryVisitDesired, DesiredWeight);
solverData.Model.SetObjective(targetFunction, GRB.MINIMIZE);
// 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];
model.AddConstr(targetFunction <= totalTimePresolved * WaytimeWeight, null);
}
var minWayTime = solverData.Input.Distances.Cast <int>().Where(i => i > 0).Min();
model.AddConstr(targetFunction >= (minWayTime * (solverData.NumberOfVisits + 1) + solverData.Input.VisitsDuration.Sum()) * (WaytimeWeight - DesiredWeight), null);
PrintDebugRessourcesAfter();
}
/// <summary>
/// Cria todas as restrições relativas às horas regulares de trabalho disponíveis
/// </summary>
/// <param name="entrada">Instância de <see cref="EntradaViewModel"/> contendo os dados informados na planilha de dados</param>
private void CriaRestricaoHE(EntradaViewModel entrada)
{
foreach (var diaSemana in Enum.GetValues(typeof(DiaDaSemana)))
{
var diaSemanaEnum = (DiaDaSemana)diaSemana;
var expressaoLinear = new GRBLinExpr();
var cargaHorariaExtraDisponivelDiaria = entrada.CargaHorariaExtraDisponivel[diaSemanaEnum];
entrada.Produtos.ForEach(produto =>
{
var taxaProducao = produto.GetTaxaUnidadeHora();
var variavelProduto = _varArray[produto.GetNomeVariavel(diaSemanaEnum, true)];
expressaoLinear.AddTerm(taxaProducao, variavelProduto);
});
_grbModel.AddConstr(
expressaoLinear,
GRB.LESS_EQUAL,
cargaHorariaExtraDisponivelDiaria,
$"HorasExtrasDisponiveis[{diaSemana}]"
);
}
}
/// <summary>
/// Basicly the same as DesiredOverlap but with unavailable
/// </summary>
/// <param name="model"></param>
/// <param name="numberOfRoutes"></param>
/// <param name="v"></param>
/// <param name="w"></param>
/// <param name="c"></param>
/// <param name="unavailableDuration"></param>
private void UnavailableOverlap(GRBModel model, int numberOfRoutes, GRBVar[][] v, GRBVar[][] w, GRBVar[][] c, GRBVar[][][] unavailableDuration, bool hardConstraint = false)
{
for (int s = 0; s < numberOfRoutes; s++)
{
var day = s / input.Santas.Length;
var(dayStart, dayEnd) = input.Days[day];
var dayDuration = dayEnd - dayStart;
for (int i = 1; i < visitDurations.Length; i++)
{
var visit = input.Visits[i - 1];
for (int d = 0; d < visit.Unavailable.Length; d++)
{
// check if unavailable is on this day
var(unavailableFrom, unavailableTo) = visit.Unavailable[d];
if (unavailableTo < dayStart || unavailableFrom > dayEnd)
{
model.Remove(unavailableDuration[s][i][d]);
unavailableDuration[s][i][d] = null;
//model.AddConstr(unavailableDuration[s][i][d] == 0, GurobiVarName($"unavailalbe[{s}][{i}][{d}] == 0, outside of day"));
continue;
}
// temp
if (hardConstraint)
{
model.AddConstr(unavailableDuration[s][i][d] == 0, GurobiVarName($"unavailalbe[{s}][{i}][{d}] == 0, hard constraint"));
}
var maxUnavailableDuration = Math.Min(visit.Duration, unavailableTo - unavailableFrom);
model.AddConstr(unavailableDuration[s][i][d] <= maxUnavailableDuration * v[s][i], GurobiVarName($"unavailable[{s}][{i}][{d}] only possible if v[{s}][{i}]"));
var unavailableStart = model.AddVar(unavailableFrom - dayStart, dayDuration, 0, GRB.CONTINUOUS, GurobiVarName($"unavailableStart[{s}][{i}][{d}]"));
var binHelperStart = model.AddVar(0, 1, 0, GRB.BINARY, GurobiVarName($"binHelperUnavailableStart[{s}][{i}][{d}]"));
var visitStart = c[s][i];
model.AddConstr(unavailableStart >= visitStart, null);
model.AddGenConstrIndicator(binHelperStart, 0, unavailableStart <= unavailableFrom - dayStart, null);
model.AddGenConstrIndicator(binHelperStart, 1, unavailableStart <= visitStart, null);
var unavailableEnd = model.AddVar(0, unavailableTo - dayStart, 0, GRB.CONTINUOUS, GurobiVarName($"unavailableEnd[{s}][{i}][{d}]"));
var binHelperEnd = model.AddVar(0, 1, 0, GRB.BINARY, GurobiVarName($"binHelperUnavailableEnd[{s}][{i}][{d}]"));
var visitEnd = visitStart + visit.Duration * v[s][i];
model.AddConstr(unavailableEnd <= visitEnd, GurobiVarName($"unavailableEnd[{s}[{i}][{d}] <= visitEnd"));
model.AddGenConstrIndicator(binHelperEnd, 0, unavailableEnd >= unavailableTo - dayStart, null);
model.AddGenConstrIndicator(binHelperEnd, 1, unavailableEnd >= visitEnd, null);
model.AddConstr(
unavailableDuration[s][i][d] >= unavailableEnd - unavailableStart,
GurobiVarName($"unavailable overlap[{s}][{i}][{d}]"));
}
}
}
}
// If the solution space is very large, this method will not return.
// The most likely result is that it will exceed memory capacity
// and then fail. As a result, we shouldn't use this method in
// any production optimization.
public IEnumerable <ProductionTarget> GetFeasibleTargets(double claySupply, double glazeSupply)
{
List <ProductionTarget> targets = new List <ProductionTarget>();
// Setup the Gurobi environment & Model
GRBEnv env = new GRBEnv();
GRBModel model = new GRBModel(env);
// Setup the decision variables
GRBVar xS = CreateSmallVasesVariable(claySupply, model);
GRBVar xL = CreateLargeVasesVariable(glazeSupply, model);
model.Update();
// Create Constraints
CreateConstraints(model, xS, xL, claySupply, glazeSupply);
// Find the greatest number of small vases we can make
var maxSmall = System.Math.Min(claySupply, glazeSupply);
// Find the greatest number of large vases we can make
var maxLarge = System.Math.Min(claySupply / 4.0, glazeSupply / 2.0);
// Find all feasible combinations of small and large vases
// Note: There are probably several better ways of doing this
// that are more efficient and organic. For example, we could make
// a tree that represents all of the possible decisions and let the
// optimizer find the solutions from within that tree.
var results = new List <ProductionTarget>();
for (int nSmall = 0; nSmall <= maxSmall; nSmall++)
{
for (int nLarge = 0; nLarge <= maxLarge; nLarge++)
{
// Force the solution to the target set of values
var c1 = model.AddConstr(xS == nSmall, $"xS_Equals_{nSmall}");
var c2 = model.AddConstr(xL == nLarge, $"xL_Equals_{nLarge}");
model.Update();
// See if the solution is feasible with those values
model.Optimize();
if (model.IsFeasible())
{
results.Add(new ProductionTarget()
{
Small = nSmall, Large = nLarge
});
}
model.Remove(c1);
model.Remove(c2);
model.Update();
}
}
return(results);
}
private void btnModelo2_Click(object sender, EventArgs e)
{
GRBEnv Ambinte = new GRBEnv();
GRBModel Modelo = new GRBModel(Ambinte);
Random Aleatorio = new Random(4);
int m = 1600;
GRBVar[,] X = new GRBVar[m, m];
for (int i = 0; i < m; i++)
{
for (int j = 0; j < m; j++)
{
X[i, j] = Modelo.AddVar(0, 1, Aleatorio.Next(1, 20), GRB.BINARY, "x_" + i.ToString() + "_" + j.ToString());
}
}
Modelo.ModelSense = GRB.MAXIMIZE;
GRBLinExpr Expressao = new GRBLinExpr();
for (int i = 0; i < m; i++)
{
Expressao.Clear();
for (int j = 0; j < m; j++)
{
Expressao.AddTerm(1, X[i, j]);
}
Modelo.AddConstr(Expressao == 1, "Vendedor_" + i);
}
for (int j = 0; j < m; j++)
{
Expressao.Clear();
for (int i = 0; i < m; i++)
{
Expressao.AddTerm(1, X[i, j]);
}
Modelo.AddConstr(Expressao == 1, "Regiao_" + j);
}
Stopwatch Cronometro = new Stopwatch();
Cronometro.Start();
Modelo.Optimize();
Cronometro.Stop();
MessageBox.Show("O valor do lucro é: " + Modelo.ObjVal.ToString());
MessageBox.Show("O tempo para resolver foi de: " + Cronometro.ElapsedMilliseconds.ToString() + " ms");
MessageBox.Show("Se quiser saber a alocação que gera esse lucro é só me pagar");
//for (int j = 0; j < m; j++)
//{
// for (int i = 0; i < m; i++)
// {
// if(X[i,j].X>0)
// {
// MessageBox.Show("O vendedor " + i + " é alocado para a região " + j);
// }
// }
//}
Modelo.Write("C:\\Teste\\Modelo2.lp");
}
public static GRBLinExpr MinimizeDeltaDistance(GRBModel model, GRBLinExpr value, GRBVar v, double c, string name)
{
GRBVar absAvgDelta = model.AddVar(0, double.PositiveInfinity, 0, GRB.CONTINUOUS, name + "_absval");
model.AddConstr(v - c <= absAvgDelta, name + "_v-c_bound");
model.AddConstr(c - v <= absAvgDelta, name + "_c-v_bound");
value += absAvgDelta;
return(value);
}
static void Main()
{
try {
GRBEnv env = new GRBEnv("mip1.log");
GRBModel model = new GRBModel(env);
// Create variables
GRBVar x = model.AddVar(0.0, 1.0, 0.0, GRB.BINARY, "x");
GRBVar y = model.AddVar(0.0, 1.0, 0.0, GRB.BINARY, "y");
GRBVar z = model.AddVar(0.0, 1.0, 0.0, GRB.BINARY, "z");
// Integrate new variables
model.Update();
// Set objective: maximize x + y + 2 z
model.SetObjective(x + y + 2 * z, GRB.MAXIMIZE);
// Add constraint: x + 2 y + 3 z <= 4
model.AddConstr(x + 2 * y + 3 * z <= 4.0, "c0");
// Add constraint: x + y >= 1
model.AddConstr(x + y >= 1.0, "c1");
// Optimize model
model.Optimize();
Console.WriteLine(x.Get(GRB.StringAttr.VarName)
+ " " + x.Get(GRB.DoubleAttr.X));
Console.WriteLine(y.Get(GRB.StringAttr.VarName)
+ " " + y.Get(GRB.DoubleAttr.X));
Console.WriteLine(z.Get(GRB.StringAttr.VarName)
+ " " + z.Get(GRB.DoubleAttr.X));
Console.WriteLine("Obj: " + model.Get(GRB.DoubleAttr.ObjVal));
// Dispose of model and env
model.Dispose();
env.Dispose();
} catch (GRBException e) {
Console.WriteLine("Error code: " + e.ErrorCode + ". " + e.Message);
}
}
static void Main()
{
try {
GRBEnv env = new GRBEnv("mip1.log");
GRBModel model = new GRBModel(env);
// Create variables
GRBVar x = model.AddVar(0.0, 1.0, 0.0, GRB.BINARY, "x");
GRBVar y = model.AddVar(0.0, 1.0, 0.0, GRB.BINARY, "y");
GRBVar z = model.AddVar(0.0, 1.0, 0.0, GRB.BINARY, "z");
// Integrate new variables
model.Update();
// Set objective: maximize x + y + 2 z
model.SetObjective(x + y + 2 * z, GRB.MAXIMIZE);
// Add constraint: x + 2 y + 3 z <= 4
model.AddConstr(x + 2 * y + 3 * z <= 4.0, "c0");
// Add constraint: x + y >= 1
model.AddConstr(x + y >= 1.0, "c1");
// Optimize model
model.Optimize();
Console.WriteLine(x.Get(GRB.StringAttr.VarName)
+ " " + x.Get(GRB.DoubleAttr.X));
Console.WriteLine(y.Get(GRB.StringAttr.VarName)
+ " " + y.Get(GRB.DoubleAttr.X));
Console.WriteLine(z.Get(GRB.StringAttr.VarName)
+ " " + z.Get(GRB.DoubleAttr.X));
Console.WriteLine("Obj: " + model.Get(GRB.DoubleAttr.ObjVal));
// Dispose of model and env
model.Dispose();
env.Dispose();
} catch (GRBException e) {
Console.WriteLine("Error code: " + e.ErrorCode + ". " + e.Message);
}
}
private void AllVehiclesMustEndAtTheDepot()
{
for (int v = 0; v < _vehicles.Count; v++)
{
var vehicleEnd = new GRBLinExpr();
for (int s = 0; s < _vertices.Count; s++)
{
vehicleEnd.AddTerm(1.0, _vehicleTraverse[v][s][_vertices.Count - 1]);
}
_model.AddConstr(vehicleEnd, GRB.EQUAL, 1.0, "_AllVehiclesMustEndAtTheDepot");
}
}
public string Example()
{
StringBuilder sb = new StringBuilder();
try
{
//GRBEnv env = new GRBEnv("mip1.log");
GRBEnv env = new GRBEnv();
GRBModel model = new GRBModel(env);
GRBVar x = model.AddVar(0.0, 1.0, 0.0, GRB.BINARY, "x");
GRBVar y = model.AddVar(0.0, 1.0, 0.0, GRB.BINARY, "y");
GRBVar z = model.AddVar(0.0, 1.0, 0.0, GRB.BINARY, "z");
// Set objective: maximize x + y + 2 z
model.SetObjective(x + y + 2 * z, GRB.MAXIMIZE);
// Add constraint: x + 2 y + 3 z <= 4
model.AddConstr(x + 2 * y + 3 * z <= 4.0, "c0");
// Add constraint: x + y >= 1
model.AddConstr(x + y >= 1.0, "c1");
// Optimize model
model.Optimize();
sb.AppendLine(x.VarName + " " + x.X);
sb.AppendLine(y.VarName + " " + y.X);
sb.AppendLine(z.VarName + " " + z.X);
sb.AppendLine("Obj: " + model.ObjVal);
// Dispose of model and env
model.Dispose();
env.Dispose();
}
catch (GRBException e)
{
//pokemon
}
return(sb.ToString());
}
static void SolveDual2(GRBEnv env, HashSet <string> nodes_set, List <Arc> arcs)
{
GRBModel dual = new GRBModel(env);
Dictionary <string, GRBLinExpr> lhs = new Dictionary <string, GRBLinExpr>();
Dictionary <string, GRBConstr> flow_balance = new Dictionary <string, GRBConstr>();
Dictionary <Arc, GRBVar> arc_traversed = new Dictionary <Arc, GRBVar>();
foreach (string node in nodes_set)
{
lhs[node] = new GRBLinExpr();
}
foreach (Arc a in arcs)
{
GRBVar var = dual.AddVar(0, 1, a.length, GRB.CONTINUOUS, "arc_traversed." + a.source + "_" + a.dest);
lhs[a.source].AddTerm(-1, var);
lhs[a.dest].AddTerm(1, var);
}
dual.Update();
foreach (string node in nodes_set)
{
flow_balance[node] = dual.AddConstr(lhs[node], 'E', 0, "flow_balance." + node);
}
dual.Update();
flow_balance[ORIGIN].Set(GRB.DoubleAttr.RHS, -1);
flow_balance[DESTINATION].Set(GRB.DoubleAttr.RHS, 1);
dual.Optimize();
dual.Dispose();
}
/// <summary>
/// I used this Gurobi model to calculate the fixed point baseline.
/// </summary>
public mae_sdo()
{
string path = @"C:\Users\Roman Bolzern\Desktop\D4\neu\meta_data_training.csv";
var lines = File.ReadLines(path).ToArray();
GRBEnv env = new GRBEnv();
GRBModel m = new GRBModel(env);
var scale = 1e9;
var y = m.AddVar(1e-9 * scale, 1e-2 * scale, 0d, GRB.CONTINUOUS, "y");
var obj = new GRBLinExpr();
for (int i = 1; i < lines.Length; i++)
{
var diff = double.Parse(lines[i].Split(',')[3]) * scale - y;
var diffinput = m.AddVar(-1e-2 * scale, 1e-2 * scale, 0d, GRB.CONTINUOUS, "diffinput");
m.AddConstr(diffinput == diff);
var diffres = m.AddVar(0, 1e-2 * scale, 0d, GRB.CONTINUOUS, "diffres");
m.AddGenConstrAbs(diffres, diffinput, "diffAbs");
obj += diffres;
}
m.SetObjective(obj, GRB.MINIMIZE);
m.Optimize();
Console.WriteLine($"Objective: {((GRBLinExpr)m.GetObjective()).Value / scale}");
Console.WriteLine($"fixed point: {y.X / scale}");
}
private void MinRouteSmallerThanMaxRoute(GRBModel model, GRBVar[] minRoutes, GRBVar[] maxRoutes)
{
for (int s = 0; s < minRoutes.Length; s++)
{
model.AddConstr(minRoutes[s] <= maxRoutes[s], GurobiVarName($"minRoutesSmallerThanMaxRoutesForSanta{s}"));
}
}
private void AddDoNotSeatOutOfBoundsConstraint(GRBModel model, GRBVar[,,] seated)
{
for (int x = 0; x < Cinema.Width; x++)
{
for (int y = 0; y < Cinema.Height; y++)
{
for (int g = 0; g < Cinema.TotalNumberOfGroups; g++)
{
var anyZeroes = false;
for (int i = 0; i < Cinema.GroupSizes[g]; i++)
{
if (x + i >= Cinema.Width || Cinema.Seats[x + i, y] == 0)
{
anyZeroes = true;
break;
}
}
if (anyZeroes)
{
model.AddConstr(seated[x, y, g], GRB.LESS_EQUAL, 0, "Out of bounds constraint");
}
}
}
}
}
private void AddDistanceConstraints(GRBModel model, GRBVar[,,] seated)
{
for (int g1 = 0; g1 < Cinema.TotalNumberOfGroups; g1++)
{
for (int g2 = 0; g2 < Cinema.TotalNumberOfGroups; g2++)
{
if (g1 < g2)
{
var size1 = Cinema.GroupSizes[g1];
var size2 = Cinema.GroupSizes[g2];
// Loop over all legal start positions for group 1
foreach (var pos1 in Cinema.LegalStartPositions[size1 - 1])
{
var x1 = pos1.Item1;
var y1 = pos1.Item2;
// Collect invalid seats
var invalidSeats = Cinema.GetInvalidSeats(x1, y1, size1, size2);
foreach (var pos2 in invalidSeats)
{
if (Cinema.LegalStartPositions[size2 - 1].Any(m => m == pos2))
{
var x2 = pos2.Item1;
var y2 = pos2.Item2;
model.AddConstr(seated[x1, y1, g1] + seated[x2, y2, g2], GRB.LESS_EQUAL, 1, "Distance constaint");
}
}
}
}
}
}
}
private void AddTargetFunction()
{
PrintDebugRessourcesBefore("AddTargetFunction");
var targetFunction = new GRBLinExpr(0);
var hour = 3600;
var longestDay = model.AddVar(0, int.MaxValue, 0, GRB.INTEGER, "longest day");
var workingTimeSum = new GRBLinExpr(0);
foreach (var santa in Enumerable.Range(0, solverData.NumberOfSantas))
{
var santaWorkingTime = solverData.Variables.SantaVisitTime[santa] + solverData.Variables.SantaRouteCost[santa];
model.AddConstr(longestDay >= santaWorkingTime, null);
workingTimeSum += santaWorkingTime;
}
var workingTimeFactor = (40d / hour);
var longestDayFactor = (30d / hour);
targetFunction = workingTimeFactor * workingTimeSum
+ longestDayFactor * longestDay;
solverData.Model.SetObjective(targetFunction, GRB.MINIMIZE);
PrintDebugRessourcesAfter();
}
private void BreakHandling(GRBModel model, int numberOfRoutes, GRBVar[][] v)
{
for (int i = 1; i < visitDurations.Length; i++)
{
if (!input.Visits[i - 1].IsBreak)
{
continue;
}
var visit = input.Visits[i - 1];
var breakRoutes = new List <int>();
for (var day = 0; day < input.Days.Length; day++)
{
var s = visit.SantaId + day * input.Santas.Length;
model.AddGenConstrOr(v[s][i], v[s].Take(i - 1).Skip(1).ToArray(), null); // assignment if used
breakRoutes.Add(s);
}
// break cannot be visited by another santa
foreach (var nonBreakRoute in Enumerable.Range(0, numberOfRoutes).Except(breakRoutes))
{
model.AddConstr(v[nonBreakRoute][i] == 0, null);
}
}
}
private void BuildConstr()
{
foreach (Node n in Frmk.Data.NodeSet)
{
GRBVar alpha = _model.GetVarByName("alpha_" + n.ID);
GRBVar beta = _model.GetVarByName("beta_" + n.ID);
_model.AddConstr(-alpha + beta <= 0, "ct_g_" + n.ID);
}
foreach (Arc a in Frmk.Data.ArcSet)
{
GRBVar fromBeta = _model.GetVarByName("beta_" + a.FromNode.ID);
GRBVar toBeta = _model.GetVarByName("beta_" + a.ToNode.ID);
GRBVar gamma = _model.GetVarByName("gamma_" + a.FromNode.ID + "_" + a.ToNode.ID);
_model.AddConstr(-fromBeta + toBeta - gamma <= Frmk.Data.FlowFeePerUnit, "ct_f+_" + a.FromNode.ID + "_" + a.ToNode.ID);
_model.AddConstr(fromBeta - toBeta - gamma <= Frmk.Data.FlowFeePerUnit, "ct_f-_" + a.FromNode.ID + "_" + a.ToNode.ID);
}
}
private void btnOi_Click(object sender, EventArgs e)
{
GRBEnv Ambiente = new GRBEnv();
GRBModel Modelo = new GRBModel(Ambiente);
GRBVar x = Modelo.AddVar(0, 1, 0, GRB.BINARY, "x");
GRBVar y = Modelo.AddVar(0, 1, 0, GRB.BINARY, "y");
GRBVar z = Modelo.AddVar(0, 1, 0, GRB.BINARY, "z");
Modelo.SetObjective(x + y + 2 * z, GRB.MAXIMIZE);
Modelo.AddConstr(x + 2 * y + 3 * z <= 4.0, "c0");
Modelo.AddConstr(x + y >= 1.0, "c1");
Modelo.Write("C:\\Teste\\ModeloAula.lp");
Modelo.Optimize();
MessageBox.Show("O valor da variável x é: " + x.X.ToString());
MessageBox.Show("O valor da variável y é: " + y.X.ToString());
MessageBox.Show("O valor da variável z é: " + z.X.ToString());
}
private void BuildConst_SG()
{
GRBLinExpr expr = 0;
foreach (Node n in Data.NodeSet)
{
expr += _grbModel_SchemeGenerateSub.GetVarByName("y_" + n.ID);
}
_grbModel_SchemeGenerateSub.AddConstr(expr >= 1, "ct_1");
/*分支定界的约束*/
foreach (Node n in CurrentBranchNode.ConstrPool.Keys)
{
GRBVar var = _grbModel_SchemeGenerateSub.GetVarByName("y_" + n.ID);
_grbModel_SchemeGenerateSub.AddConstr(var == CurrentBranchNode.ConstrPool[n], "ct_2" + "_" + n.ID);
}
}
public void mip1_cs()
{
try
{
// Create an empty environment, set options and start
GRBEnv env = new GRBEnv(true);
env.Set("LogFile", "mip1.log");
env.Start();
// Create empty model
GRBModel model = new GRBModel(env);
// Create variables
GRBVar x = model.AddVar(0.0, 1.0, 1.0, GRB.BINARY, "x");
GRBVar y = model.AddVar(0.0, 1.0, 1.0, GRB.BINARY, "y");
GRBVar z = model.AddVar(0.0, 1.0, 1.0, GRB.BINARY, "z");
// Set objective: maximize x + y + 2 z
model.SetObjective(x + y + 2 * z, GRB.MAXIMIZE);
// Add constraint: x + 2 y + 3 z <= 4
model.AddConstr(x + 2 * y + 3 * z <= 4.0, "c0");
// Add constraint: x + y >= 1
model.AddConstr(x + y >= 1.0, "c1");
// Optimize model
model.Optimize();
Console.WriteLine(x.VarName + " " + x.X);
Console.WriteLine(y.VarName + " " + y.X);
Console.WriteLine(z.VarName + " " + z.X);
Console.WriteLine("Obj: " + model.ObjVal);
// Dispose of model and env
model.Dispose();
env.Dispose();
}
catch (GRBException e)
{
Console.WriteLine("Error code: " + e.ErrorCode + ". " + e.Message);
}
}
private void DesiredOverlap(GRBModel model, int numberOfRoutes, GRBVar[][] v, GRBVar[][] w, GRBVar[][] c, GRBVar[][][] desiredDuration)
{
for (int s = 0; s < numberOfRoutes; s++)
{
var day = s / input.Santas.Length;
var(dayStart, dayEnd) = input.Days[day];
var dayDuration = dayEnd - dayStart;
for (int i = 1; i < visitDurations.Length; i++)
{
var visit = input.Visits[i - 1];
for (int d = 0; d < visit.Desired.Length; d++)
{
var(desiredFrom, desiredTo) = visit.Desired[d];
// check if desired on day
if (desiredTo < dayStart || desiredFrom > dayEnd)
{
model.Remove(desiredDuration[s][i][d]);
desiredDuration[s][i][d] = null; //free up memory
//model.AddConstr(desiredDuration[s][i][d] == 0, GurobiVarName($"desiredDuration[{s}][{i}][{d}] == 0, outside of day"));
continue;
}
var maxDesiredDuration = Math.Min(visit.Duration, desiredTo - desiredFrom);
model.AddConstr(desiredDuration[s][i][d] <= maxDesiredDuration * v[s][i], GurobiVarName($"desired[{s}][{i}][{d}] only possible if v[{s}][{i}]"));
var desiredStart = model.AddVar(Math.Max(desiredFrom - dayStart, 0), dayDuration, 0, GRB.CONTINUOUS, GurobiVarName($"desiredStart[{s}][{i}][{d}]"));
model.AddConstr(desiredStart >= c[s][i], GurobiVarName($"desiredStart[{s}[{i}][{d}] >= visitStart"));
var desiredEnd = model.AddVar(0, desiredTo - dayStart, 0, GRB.CONTINUOUS, GurobiVarName($"desiredEnd[{s}][{i}][{d}]"));
model.AddConstr(desiredEnd <= c[s][i] + visit.Duration * v[s][i], GurobiVarName($"desiredEnd[{s}[{i}][{d}] <= visitEnd"));
var binDecisionVariable = model.AddVar(0, 1, 0, GRB.BINARY, GurobiVarName($"binDesiredDecisionVar[{s}][{i}][{d}]"));
// if positive, duration = end -start
model.AddGenConstrIndicator(binDecisionVariable, 0, desiredEnd - desiredStart >= 0, null);
model.AddGenConstrIndicator(binDecisionVariable, 0, desiredDuration[s][i][d] == desiredEnd - desiredStart, null);
// if negative, duration = 0
model.AddGenConstrIndicator(binDecisionVariable, 1, desiredEnd - desiredStart <= 0, null);
model.AddGenConstrIndicator(binDecisionVariable, 1, desiredDuration[s][i][d] == 0, null);
}
}
}
}
private void BuildConst_SG()
{
GRBLinExpr expr = 0;
foreach (Node n in Data.NodeSet)
{
expr += _grbModel_SchemeGenerateSub.GetVarByName("y_" + n.ID);
}
_grbModel_SchemeGenerateSub.AddConstr(expr >= 1, "ct_1");
}
public static Graph RunSolver(Graph graph)
{
GRBEnv env = new GRBEnv();
env.Set(GRB.IntParam.OutputFlag, 0);
env.Set(GRB.IntParam.LogToConsole, 0);
env.Set(GRB.IntParam.Presolve, 2);
env.Set(GRB.DoubleParam.Heuristics, 0.0);
GRBModel model = new GRBModel(env);
GRBVar[] variables = new GRBVar[graph.NumberOfEdges];
model.SetCallback(new LPSolverCallback());
Dictionary<Edge, GRBVar> edgeVars = new Dictionary<Edge, GRBVar>();
// Add variables to the LP model
for (int i = 0; i < graph.NumberOfEdges; i++)
{
variables[i] = model.AddVar(0.0, 1.0, 0.0, GRB.BINARY, "x_" + i);
edgeVars.Add(graph.Edges[i], variables[i]);
}
model.Update();
// Add constraints to the LP model
Console.Write("\rRunning LP. Creating constraints...\r");
//var nonTerminals = graph.Vertices.Except(graph.Terminals).ToList();
ulong conNr = 0;
//var terminalCombinations = new List<List<Vertex>>();
// Assume, without loss of generality, that Terminals[0] is the root, and thus is always included
int rootNr = 1;
foreach (var rootTerminal in graph.Terminals)
//var rootTerminal = graph.Terminals[0];
{
Console.Write("\rRunning LP. Creating constraints... {0}/{1}\r", rootNr, graph.Terminals.Count);
foreach (var combination in GetBFS(graph, rootTerminal))
{
var nodes = combination.ToList(); //new HashSet<Vertex>(combination);
if (nodes.Count == graph.NumberOfVertices || graph.Terminals.All(nodes.Contains))
continue;
//Debug.WriteLine("Combination: {0}", string.Join(" ", nodes));
//for (int i = 1; i <= nodes.Count; i++)
{
var edges = nodes//.Take(i)
.SelectMany(graph.GetEdgesForVertex)
.Distinct()
.Where(x => x.WhereOne(y => !nodes.Contains(y)));
GRBLinExpr expression = 0;
foreach (var edge in edges)
expression.AddTerm(1, edgeVars[edge]);
model.AddConstr(expression >= 1.0, "subset_" + conNr);
conNr++;
if (conNr % 100000 == 0)
{
//model = model.Presolve(); //Pre-solve the model every 1000 constraints.
int constrBefore = model.GetConstrs().Length, varsBefore = model.GetVars().Length;
Debug.WriteLine("Presolve called.");
var presolved = model.Presolve();
Debug.WriteLine("Model has {0} constraints, {1} variables. Presolve has {2} constraints, {3} variables",
constrBefore, varsBefore, presolved.GetConstrs().Length, presolved.GetVars().Length);
}
}
}
//Debug.WriteLine(" ");
//Debug.WriteLine(" ");
rootNr++;
}
//terminalCombinations.Add(new List<Vertex>(new[] { graph.Terminals[0] }));
//for (int j = 1; j < graph.Terminals.Count - 1; j++)
// terminalCombinations.AddRange(new Combinations<Vertex>(graph.Terminals.Skip(1), j).Select(combination => combination.Union(new[] { graph.Terminals[0] }).ToList()));
//long nonTerminalSetsDone = 0;
//long nonTerminalSets = 0;
//for (int i = 0; i <= nonTerminals.Count; i++)
// nonTerminalSets += Combinations<Vertex>.NumberOfCombinations(nonTerminals.Count, i);
//for (int i = 0; i <= nonTerminals.Count; i++)
//{
// foreach (var nonTerminalSet in new Combinations<Vertex>(nonTerminals, i))
// {
// foreach (var nodes in (from a in terminalCombinations
// select new HashSet<Vertex>(a.Union(nonTerminalSet))))
// {
// var edges = nodes.SelectMany(graph.GetEdgesForVertex)
// .Distinct()
// .Where(x => x.WhereOne(y => !nodes.Contains(y)));
// GRBLinExpr expression = 0;
// foreach (var edge in edges)
// expression.AddTerm(1, edgeVars[edge]);
// model.AddConstr(expression >= 1.0, "subset_" + conNr);
// conNr++;
// }
// nonTerminalSetsDone++;
// if (nonTerminalSetsDone % 100 == 0)
// Console.Write("\rRunning LP. Creating constraints... {0}/{1} ({2:0.000}%)\r", nonTerminalSetsDone, nonTerminalSets, nonTerminalSetsDone * 100.0 / nonTerminalSets);
// }
//}
// Solve the LP model
Console.Write("\rRunning LP. Creating objective & updating... \r");
GRBLinExpr objective = new GRBLinExpr();
for (int i = 0; i < graph.NumberOfEdges; i++)
objective.AddTerm(graph.Edges[i].Cost, variables[i]);
model.SetObjective(objective, GRB.MINIMIZE);
Console.Write("\rRunning LP. Tuning... \r");
model.Tune();
Debug.WriteLine("Presolve called.");
model.Presolve();
Console.Write("\rRunning LP. Solving... \r");
Debug.WriteLine("Optimize called.");
model.Optimize();
Graph solution = graph.Clone();
HashSet<Edge> includedEdges = new HashSet<Edge>();
for (int i = 0; i < solution.NumberOfEdges; i++)
{
var value = variables[i].Get(GRB.DoubleAttr.X);
if (value == 1)
includedEdges.Add(solution.Edges[i]);
}
foreach (var edge in solution.Edges.ToList())
if (!includedEdges.Contains(edge))
solution.RemoveEdge(edge);
Console.Write("\r \r");
return solution;
}
static void Main()
{
try {
// Sample data
// Sets of days and workers
string[] Shifts =
new string[] { "Mon1", "Tue2", "Wed3", "Thu4", "Fri5", "Sat6",
"Sun7", "Mon8", "Tue9", "Wed10", "Thu11", "Fri12", "Sat13",
"Sun14" };
string[] Workers =
new string[] { "Amy", "Bob", "Cathy", "Dan", "Ed", "Fred", "Gu" };
int nShifts = Shifts.Length;
int nWorkers = Workers.Length;
// Number of workers required for each shift
double[] shiftRequirements =
new double[] { 3, 2, 4, 4, 5, 6, 5, 2, 2, 3, 4, 6, 7, 5 };
// Amount each worker is paid to work one shift
double[] pay = new double[] { 10, 12, 10, 8, 8, 9, 11 };
// Worker availability: 0 if the worker is unavailable for a shift
double[,] availability =
new double[,] { { 0, 1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1 },
{ 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 0 },
{ 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1 },
{ 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1 },
{ 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1 },
{ 1, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1 },
{ 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 } };
// Model
GRBEnv env = new GRBEnv();
GRBModel model = new GRBModel(env);
model.Set(GRB.StringAttr.ModelName, "assignment");
// Assignment variables: x[w][s] == 1 if worker w is assigned
// to shift s. Since an assignment model always produces integer
// solutions, we use continuous variables and solve as an LP.
GRBVar[,] x = new GRBVar[nWorkers,nShifts];
for (int w = 0; w < nWorkers; ++w) {
for (int s = 0; s < nShifts; ++s) {
x[w,s] =
model.AddVar(0, availability[w,s], pay[w], GRB.CONTINUOUS,
Workers[w] + "." + Shifts[s]);
}
}
// The objective is to minimize the total pay costs
model.Set(GRB.IntAttr.ModelSense, 1);
// Update model to integrate new variables
model.Update();
// Constraint: assign exactly shiftRequirements[s] workers
// to each shift s
for (int s = 0; s < nShifts; ++s) {
GRBLinExpr lhs = 0.0;
for (int w = 0; w < nWorkers; ++w)
lhs += x[w, s];
model.AddConstr(lhs == shiftRequirements[s], Shifts[s]);
}
// Optimize
model.Optimize();
int status = model.Get(GRB.IntAttr.Status);
if (status == GRB.Status.UNBOUNDED) {
Console.WriteLine("The model cannot be solved "
+ "because it is unbounded");
return;
}
if (status == GRB.Status.OPTIMAL) {
Console.WriteLine("The optimal objective is " +
model.Get(GRB.DoubleAttr.ObjVal));
return;
}
if ((status != GRB.Status.INF_OR_UNBD) &&
(status != GRB.Status.INFEASIBLE)) {
Console.WriteLine("Optimization was stopped with status " + status);
return;
}
// Do IIS
Console.WriteLine("The model is infeasible; computing IIS");
LinkedList<string> removed = new LinkedList<string>();
// Loop until we reduce to a model that can be solved
while (true) {
model.ComputeIIS();
Console.WriteLine("\nThe following constraint cannot be satisfied:");
foreach (GRBConstr c in model.GetConstrs()) {
if (c.Get(GRB.IntAttr.IISConstr) == 1) {
Console.WriteLine(c.Get(GRB.StringAttr.ConstrName));
// Remove a single constraint from the model
removed.AddFirst(c.Get(GRB.StringAttr.ConstrName));
model.Remove(c);
break;
}
}
Console.WriteLine();
model.Optimize();
status = model.Get(GRB.IntAttr.Status);
if (status == GRB.Status.UNBOUNDED) {
Console.WriteLine("The model cannot be solved "
+ "because it is unbounded");
return;
}
if (status == GRB.Status.OPTIMAL) {
break;
}
if ((status != GRB.Status.INF_OR_UNBD) &&
(status != GRB.Status.INFEASIBLE)) {
Console.WriteLine("Optimization was stopped with status " +
status);
return;
}
}
Console.WriteLine("\nThe following constraints were removed "
+ "to get a feasible LP:");
foreach (string s in removed) {
Console.Write(s + " ");
}
Console.WriteLine();
// Dispose of model and env
model.Dispose();
env.Dispose();
} catch (GRBException e) {
Console.WriteLine("Error code: " + e.ErrorCode + ". " +
e.Message);
}
}
public Instance Match(Instance instance, string path, bool print)
{
try
{
LP = "";
if (!System.IO.Directory.Exists(path) && print)
System.IO.Directory.CreateDirectory(path);
GRBEnv env = new GRBEnv("mip1.log");
GRBModel model = new GRBModel(env);
List<LPEdge> LPEdges = new List<LPEdge>();
if (print)
{
instance.Draw().Save(path + "/0Start.bmp");
}
int EdgeCounter = 0;
foreach (Instance.Applicant a in instance.Applicants)
{
EdgeCounter += a.Priorities.Count;
foreach (Instance.Priority Prio in a.Priorities)
{
{
LPEdges.Add(new LPEdge(a, instance.Posts[Prio.Target], Prio.Rank));
if (Prio.Rank == 0)
instance.Posts[Prio.Target].IsF = 1;
}
}
}
// Create variables
GRBVar[] Edges = new GRBVar[EdgeCounter];
for (int i = 0; i < Edges.Length; i++)
{
Edges[i] = model.AddVar(0.0, 1.0, 0.0, GRB.BINARY, "ve" + i.ToString());
}
// Integrate new variables
model.Update();
if (print)
LP += "Applicant Matching Conditions:" + Environment.NewLine;
foreach (Instance.Applicant a in instance.Applicants)
{
GRBLinExpr Temp = new GRBLinExpr();
for (int i = 0; i < LPEdges.Count; i++)
{
if (LPEdges[i].Applicant == a)
{
Temp += Edges[i];
if (print)
LP += "(a" + LPEdges[i].Applicant.ID + ", p" + LPEdges[i].Post.ID + ") + ";
}
}
model.AddConstr(Temp == 1.0, "a" + a.ID.ToString());
if (print)
LP += " = 1;" + Environment.NewLine;
}
if (print)
LP += Environment.NewLine + "Post Matching Conditions:" + Environment.NewLine;
foreach (Instance.Post p in instance.Posts)
{
GRBLinExpr Temp = new GRBLinExpr();
for (int i = 0; i < LPEdges.Count; i++)
{
if (LPEdges[i].Post == p)
{
Temp += Edges[i];
if (print)
LP += "(a" + LPEdges[i].Applicant.ID + ", p" + LPEdges[i].Post.ID + ") + ";
}
}
model.AddConstr(Temp <= 1.0, "p" + p.ID.ToString());
if (print)
LP += " <= 1;" + Environment.NewLine;
}
if (print)
LP += Environment.NewLine + "First Choice Conditions:" + Environment.NewLine;
for (int i = 0; i < LPEdges.Count; i++)
{
LPEdge le1 = LPEdges[i];
if (le1.Post.IsF == 1 && le1.Rank != 0)
{
model.AddConstr(Edges[i] <= 0, "s" + i.ToString());
if (print)
LP += "(a" + LPEdges[i].Applicant.ID + ", p" + LPEdges[i].Post.ID + ") <= 0;" + Environment.NewLine;
for (int j = 0; j < LPEdges[i].Applicant.Priorities.Count; j++)
{
if (LPEdges[i].Applicant.Priorities[j].Target == LPEdges[i].Post.ID && LPEdges[i].Rank == LPEdges[i].Applicant.Priorities[j].Rank)
{
LPEdges[i].Applicant.Priorities.RemoveAt(j);
}
}
}
}
if (print)
LP += Environment.NewLine + "Second Choice Conditions:" + Environment.NewLine;
for (int i = 0; i < LPEdges.Count; i++)
{
LPEdge le1 = LPEdges[i];
foreach (LPEdge le2 in LPEdges)
{
if (le2 != le1 && le2.Post.IsF == 0 && le1.Applicant == le2.Applicant && le2.Rank != 0 && le2.Rank < le1.Rank)
{
model.AddConstr(Edges[i] <= 0, "s" + i.ToString());
if (print)
LP += "(a" + LPEdges[i].Applicant.ID + ", p" + LPEdges[i].Post.ID + ") <= 0;" + Environment.NewLine;
for (int j = 0; j < LPEdges[i].Applicant.Priorities.Count; j++)
{
if (LPEdges[i].Applicant.Priorities[j].Target == LPEdges[i].Post.ID && LPEdges[i].Rank == LPEdges[i].Applicant.Priorities[j].Rank)
{
LPEdges[i].Applicant.Priorities.RemoveAt(j);
}
}
break;
}
}
}
if (print)
LP += Environment.NewLine + "First Post Conditions:" + Environment.NewLine;
foreach (Instance.Post p in instance.Posts)
{
if (p.IsF == 1)
{
GRBLinExpr Temp = new GRBLinExpr();
for (int i = 0; i < LPEdges.Count; i++)
{
if (LPEdges[i].Post == p)
{
Temp += Edges[i];
if (print)
LP += "(a" + LPEdges[i].Applicant.ID + ", p" + LPEdges[i].Post.ID + ") + ";
}
}
model.AddConstr(Temp >= 1.0, "f" + p.ID.ToString());
if (print)
LP += ">= 1;" + Environment.NewLine;
}
}
// Optimize model
model.Optimize();
if (print)
{
instance.Draw().Save(path + "/1Reduced.bmp");
}
for (int i = 0; i < Edges.Length; i++)
{
if (Edges[i].Get(GRB.DoubleAttr.X) == 1)
{
instance.AddMatch(LPEdges[i].Post.ID, LPEdges[i].Applicant.ID);
}
}
if (print)
{
instance.Draw().Save(path + "/2Matched.bmp");
}
// Dispose of model and env
model.Dispose();
env.Dispose();
return instance;
}
catch (GRBException e)
{
Console.WriteLine("Error code: " + e.ErrorCode + ". " + e.Message);
return null;
}
}
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.Set(GRB.StringAttr.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
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
model.Set(GRB.IntAttr.ModelSense, 1);
// Update model to integrate new variables
model.Update();
// Nutrition constraints
for (int i = 0; i < nCategories; ++i) {
GRBLinExpr ntot = 0.0;
for (int j = 0; j < nFoods; ++j)
ntot += 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);
}
}
public void AddNutritionConstraints(GRBModel model)
{
// Nutrition constraints
for (int i = 0; i < NumberOfCategories; ++i)
{
GRBLinExpr ntot = 0.0;
for (int j = 0; j < numberOfFoodTypes; ++j)
ntot += nutritionValues[j, i] * boughtAmount[j];
model.AddConstr(ntot == nutritionDecisionVariables[i], categories[i]);
}
}
public void AddExtraConstraint(GRBModel model)
{
model.AddConstr(boughtAmount[7] + boughtAmount[8] <= 6.0, "limit_dairy");
}
public static void Main(String[] args)
{
if (args.Length < 1) {
Console.WriteLine("Usage: tsp_cs nnodes");
return;
}
int n = Convert.ToInt32(args[0]);
try {
GRBEnv env = new GRBEnv();
GRBModel model = new GRBModel(env);
// Must disable dual reductions when using lazy constraints
model.GetEnv().Set(GRB.IntParam.DualReductions, 0);
double[] x = new double[n];
double[] y = new double[n];
Random r = new Random();
for (int i = 0; i < n; i++) {
x[i] = r.NextDouble();
y[i] = r.NextDouble();
}
// Create variables
GRBVar[,] vars = new GRBVar[n, n];
for (int i = 0; i < n; i++)
for (int j = 0; j < n; j++)
vars[i, j] = model.AddVar(0.0, 1.0, distance(x, y, i, j),
GRB.BINARY, "x"+i+"_"+j);
// Integrate variables
model.Update();
// Degree-2 constraints
for (int i = 0; i < n; i++) {
GRBLinExpr expr = 0;
for (int j = 0; j < n; j++)
expr += vars[i, j];
model.AddConstr(expr == 2.0, "deg2_"+i);
}
// Forbid edge from node back to itself
for (int i = 0; i < n; i++)
vars[i, i].Set(GRB.DoubleAttr.UB, 0.0);
// Symmetric TSP
for (int i = 0; i < n; i++)
for (int j = 0; j < i; j++)
model.AddConstr(vars[i, j]== vars[j, i], "");
model.SetCallback(new tsp_cs(vars));
model.Optimize();
if (model.Get(GRB.IntAttr.SolCount) > 0) {
int[] tour = findsubtour(model.Get(GRB.DoubleAttr.X, vars));
Console.Write("Tour: ");
for (int i = 0; i < tour.Length; i++)
Console.Write(tour[i] + " ");
Console.WriteLine();
}
// Dispose of model and environment
model.Dispose();
env.Dispose();
} catch (GRBException e) {
Console.WriteLine("Error code: " + e.ErrorCode + ". " + e.Message);
Console.WriteLine(e.StackTrace);
}
}
static void Main()
{
try {
// Warehouse demand in thousands of units
double[] Demand = new double[] { 15, 18, 14, 20 };
// Plant capacity in thousands of units
double[] Capacity = new double[] { 20, 22, 17, 19, 18 };
// Fixed costs for each plant
double[] FixedCosts =
new double[] { 12000, 15000, 17000, 13000, 16000 };
// Transportation costs per thousand units
double[,] TransCosts =
new double[,] { { 4000, 2000, 3000, 2500, 4500 },
{ 2500, 2600, 3400, 3000, 4000 },
{ 1200, 1800, 2600, 4100, 3000 },
{ 2200, 2600, 3100, 3700, 3200 } };
// Number of plants and warehouses
int nPlants = Capacity.Length;
int nWarehouses = Demand.Length;
// Model
GRBEnv env = new GRBEnv();
GRBModel model = new GRBModel(env);
model.Set(GRB.StringAttr.ModelName, "facility");
// Plant open decision variables: open[p] == 1 if plant p is open.
GRBVar[] open = new GRBVar[nPlants];
for (int p = 0; p < nPlants; ++p) {
open[p] = model.AddVar(0, 1, FixedCosts[p], GRB.BINARY, "Open" + p);
}
// Transportation decision variables: how much to transport from
// a plant p to a warehouse w
GRBVar[,] transport = new GRBVar[nWarehouses,nPlants];
for (int w = 0; w < nWarehouses; ++w) {
for (int p = 0; p < nPlants; ++p) {
transport[w,p] =
model.AddVar(0, GRB.INFINITY, TransCosts[w,p], GRB.CONTINUOUS,
"Trans" + p + "." + w);
}
}
// The objective is to minimize the total fixed and variable costs
model.Set(GRB.IntAttr.ModelSense, 1);
// Update model to integrate new variables
model.Update();
// Production constraints
// Note that the right-hand limit sets the production to zero if
// the plant is closed
for (int p = 0; p < nPlants; ++p) {
GRBLinExpr ptot = 0.0;
for (int w = 0; w < nWarehouses; ++w)
ptot += transport[w,p];
model.AddConstr(ptot <= Capacity[p] * open[p], "Capacity" + p);
}
// Demand constraints
for (int w = 0; w < nWarehouses; ++w) {
GRBLinExpr dtot = 0.0;
for (int p = 0; p < nPlants; ++p)
dtot += transport[w,p];
model.AddConstr(dtot == Demand[w], "Demand" + w);
}
// Guess at the starting point: close the plant with the highest
// fixed costs; open all others
// First, open all plants
for (int p = 0; p < nPlants; ++p) {
open[p].Set(GRB.DoubleAttr.Start, 1.0);
}
// Now close the plant with the highest fixed cost
Console.WriteLine("Initial guess:");
double maxFixed = -GRB.INFINITY;
for (int p = 0; p < nPlants; ++p) {
if (FixedCosts[p] > maxFixed) {
maxFixed = FixedCosts[p];
}
}
for (int p = 0; p < nPlants; ++p) {
if (FixedCosts[p] == maxFixed) {
open[p].Set(GRB.DoubleAttr.Start, 0.0);
Console.WriteLine("Closing plant " + p + "\n");
break;
}
}
// Use barrier to solve root relaxation
model.GetEnv().Set(GRB.IntParam.Method, GRB.METHOD_BARRIER);
// Solve
model.Optimize();
// Print solution
Console.WriteLine("\nTOTAL COSTS: " + model.Get(GRB.DoubleAttr.ObjVal));
Console.WriteLine("SOLUTION:");
for (int p = 0; p < nPlants; ++p) {
if (open[p].Get(GRB.DoubleAttr.X) == 1.0) {
Console.WriteLine("Plant " + p + " open:");
for (int w = 0; w < nWarehouses; ++w) {
if (transport[w,p].Get(GRB.DoubleAttr.X) > 0.0001) {
Console.WriteLine(" Transport " +
transport[w,p].Get(GRB.DoubleAttr.X) +
" units to warehouse " + w);
}
}
} else {
Console.WriteLine("Plant " + p + " closed!");
}
}
// Dispose of model and env
model.Dispose();
env.Dispose();
} catch (GRBException e) {
Console.WriteLine("Error code: " + e.ErrorCode + ". " + e.Message);
}
}
protected static bool dense_optimize(GRBEnv env,
int rows,
int cols,
double[] c, // linear portion of objective function
double[,] Q, // quadratic portion of objective function
double[,] A, // constraint matrix
char[] sense, // constraint senses
double[] rhs, // RHS vector
double[] lb, // variable lower bounds
double[] ub, // variable upper bounds
char[] vtype, // variable types (continuous, binary, etc.)
double[] solution)
{
bool success = false;
try {
GRBModel model = new GRBModel(env);
// Add variables to the model
GRBVar[] vars = model.AddVars(lb, ub, null, vtype, null);
model.Update();
// Populate A matrix
for (int i = 0; i < rows; i++) {
GRBLinExpr expr = new GRBLinExpr();
for (int j = 0; j < cols; j++)
if (A[i,j] != 0)
expr.AddTerm(A[i,j], vars[j]); // Note: '+=' would be much slower
model.AddConstr(expr, sense[i], rhs[i], "");
}
// Populate objective
GRBQuadExpr obj = new GRBQuadExpr();
if (Q != null) {
for (int i = 0; i < cols; i++)
for (int j = 0; j < cols; j++)
if (Q[i,j] != 0)
obj.AddTerm(Q[i,j], vars[i], vars[j]); // Note: '+=' would be much slower
for (int j = 0; j < cols; j++)
if (c[j] != 0)
obj.AddTerm(c[j], vars[j]); // Note: '+=' would be much slower
model.SetObjective(obj);
}
// Solve model
model.Optimize();
// Extract solution
if (model.Get(GRB.IntAttr.Status) == GRB.Status.OPTIMAL) {
success = true;
for (int j = 0; j < cols; j++)
solution[j] = vars[j].Get(GRB.DoubleAttr.X);
}
model.Dispose();
} catch (GRBException e) {
Console.WriteLine("Error code: " + e.ErrorCode + ". " + e.Message);
}
return success;
}
static void Main()
{
try {
// Sample data
// Sets of days and workers
string[] Shifts =
new string[] { "Mon1", "Tue2", "Wed3", "Thu4", "Fri5", "Sat6",
"Sun7", "Mon8", "Tue9", "Wed10", "Thu11", "Fri12", "Sat13",
"Sun14" };
string[] Workers =
new string[] { "Amy", "Bob", "Cathy", "Dan", "Ed", "Fred", "Gu" };
int nShifts = Shifts.Length;
int nWorkers = Workers.Length;
// Number of workers required for each shift
double[] shiftRequirements =
new double[] { 3, 2, 4, 4, 5, 6, 5, 2, 2, 3, 4, 6, 7, 5 };
// Amount each worker is paid to work one shift
double[] pay = new double[] { 10, 12, 10, 8, 8, 9, 11 };
// Worker availability: 0 if the worker is unavailable for a shift
double[,] availability =
new double[,] { { 0, 1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1 },
{ 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 0 },
{ 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1 },
{ 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1 },
{ 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1 },
{ 1, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1 },
{ 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 } };
// Model
GRBEnv env = new GRBEnv();
GRBModel model = new GRBModel(env);
model.Set(GRB.StringAttr.ModelName, "assignment");
// Assignment variables: x[w][s] == 1 if worker w is assigned
// to shift s. Since an assignment model always produces integer
// solutions, we use continuous variables and solve as an LP.
GRBVar[,] x = new GRBVar[nWorkers,nShifts];
for (int w = 0; w < nWorkers; ++w) {
for (int s = 0; s < nShifts; ++s) {
x[w,s] =
model.AddVar(0, availability[w,s], pay[w], GRB.CONTINUOUS,
Workers[w] + "." + Shifts[s]);
}
}
// The objective is to minimize the total pay costs
model.Set(GRB.IntAttr.ModelSense, 1);
// Update model to integrate new variables
model.Update();
// Constraint: assign exactly shiftRequirements[s] workers
// to each shift s
LinkedList<GRBConstr> reqCts = new LinkedList<GRBConstr>();
for (int s = 0; s < nShifts; ++s) {
GRBLinExpr lhs = 0.0;
for (int w = 0; w < nWorkers; ++w)
lhs += x[w,s];
GRBConstr newCt =
model.AddConstr(lhs == shiftRequirements[s], Shifts[s]);
reqCts.AddFirst(newCt);
}
// Optimize
model.Optimize();
int status = model.Get(GRB.IntAttr.Status);
if (status == GRB.Status.UNBOUNDED) {
Console.WriteLine("The model cannot be solved "
+ "because it is unbounded");
return;
}
if (status == GRB.Status.OPTIMAL) {
Console.WriteLine("The optimal objective is " +
model.Get(GRB.DoubleAttr.ObjVal));
return;
}
if ((status != GRB.Status.INF_OR_UNBD) &&
(status != GRB.Status.INFEASIBLE)) {
Console.WriteLine("Optimization was stopped with status " + status);
return;
}
// Add slack variables to make the model feasible
Console.WriteLine("The model is infeasible; adding slack variables");
// Set original objective coefficients to zero
model.SetObjective(new GRBLinExpr());
// Add a new slack variable to each shift constraint so that the shifts
// can be satisfied
LinkedList<GRBVar> slacks = new LinkedList<GRBVar>();
foreach (GRBConstr c in reqCts) {
GRBColumn col = new GRBColumn();
col.AddTerm(1.0, c);
GRBVar newvar =
model.AddVar(0, GRB.INFINITY, 1.0, GRB.CONTINUOUS, col,
c.Get(GRB.StringAttr.ConstrName) + "Slack");
slacks.AddFirst(newvar);
}
// Solve the model with slacks
model.Optimize();
status = model.Get(GRB.IntAttr.Status);
if ((status == GRB.Status.INF_OR_UNBD) ||
(status == GRB.Status.INFEASIBLE) ||
(status == GRB.Status.UNBOUNDED)) {
Console.WriteLine("The model with slacks cannot be solved "
+ "because it is infeasible or unbounded");
return;
}
if (status != GRB.Status.OPTIMAL) {
Console.WriteLine("Optimization was stopped with status " + status);
return;
}
Console.WriteLine("\nSlack values:");
foreach (GRBVar sv in slacks) {
if (sv.Get(GRB.DoubleAttr.X) > 1e-6) {
Console.WriteLine(sv.Get(GRB.StringAttr.VarName) + " = " +
sv.Get(GRB.DoubleAttr.X));
}
}
// Dispose of model and env
model.Dispose();
env.Dispose();
} catch (GRBException e) {
Console.WriteLine("Error code: " + e.ErrorCode + ". " +
e.Message);
}
}
public HttpResponseMessage Optimize(string RunName)
{
using (var dbConn = new ApplicationDbContext())
{
//Variables for students, semesters, courses, and course/semester offerings
students = dbConn.StudentPreferences.Where(m => m.IsActive == true).Include(m => m.Courses).Include(m => m.Student.CompletedCourses).OrderByDescending(m => m.Student.CompletedCourses.Count()).ToArray();
crssems = dbConn.CourseSemesters.Where(m => m.IsActive == true).Include(m => m.Course).Include(m => m.Semester).ToArray();
courses = crssems.Select(m => m.Course).Distinct().ToArray();
sems = crssems.Select(m => m.Semester).Distinct().OrderBy(m => m.Type).OrderBy(m => m.Year).ToArray();
var completed = dbConn.CompletedCourses.ToList();
try
{
GRBEnv env = new GRBEnv("mip1.log");
GRBModel model = new GRBModel(env);
model.Set(GRB.StringAttr.ModelName, "Course Optimizer");
GRBVar[,] slacks = new GRBVar[courses.Length, sems.Length];
//Assignment of student, course, and semester. Student must have a desire to take the coure, has not taken the course, and the course is offered to be included
GRBVar[,,] CourseAllocation = new GRBVar[students.Length, courses.Length, sems.Length];
for (int i = 0; i < students.Length; i++)
{
for (int j = 0; j < courses.Length; j++)
{
for (int k = 0; k < sems.Length; k++)
{
if (students[i].Courses.Contains(courses[j]) && !completed.Any(m => m.GaTechId == students[i].GaTechId && courses[j].ID == m.Course_ID) && crssems.Contains(crssems.SingleOrDefault(m => m.Course == courses[j] && m.Semester == sems[k])))
CourseAllocation[i, j, k] = model.AddVar(0, 1, 1, GRB.BINARY, "students." + (i + 1).ToString() + "_Course." + (j + 1).ToString() + "_Semester." + (k + 1).ToString());
else
CourseAllocation[i, j, k] = model.AddVar(0, 0, 1, GRB.BINARY, "students." + (i + 1).ToString() + "_Course." + (j + 1).ToString() + "_Semester." + (k + 1).ToString());
}
}
}
model.Set(GRB.IntAttr.ModelSense, 1);
model.Update();
//MUST TAKE DESIRED COURSE ONLY ONCE
//Constrains the students to only take courses they desire once and for when the course is offered and does not allow a repeat of a course in another semester
for (int i = 0; i < students.Length; i++)
{
for (int j = 0; j < courses.Length; j++)
{
if (students[i].Courses.Contains(courses[j]) && !completed.Any(m => m.GaTechId == students[i].GaTechId && courses[j].ID == m.Course_ID))
{
GRBLinExpr constStudentDesiredCourses = 0.0;
for (int k = 0; k < sems.Length; k++)
{
if (crssems.Any(m => m.Course.ID == courses[j].ID && m.Semester.Type == sems[k].Type && m.Semester.Year == sems[k].Year))
constStudentDesiredCourses.AddTerm(1.0, CourseAllocation[i, j, k]);
}
String sStudentDesiredCourses = "DesiredCourse." + j + 1 + "_Student." + i + 1;
model.AddConstr(constStudentDesiredCourses == 1, sStudentDesiredCourses);
}
}
//MAX COURSES PER SEMESTER
//Constrains the students to only have a maximum number of 2 courses per semester.
for (int k = 0; k < sems.Length; k++)
{
GRBLinExpr constMaxPerSem = 0.0;
for (int j = 0; j < courses.Length; j++)
{
if (!completed.Any(m => m.GaTechId == students[i].GaTechId && courses[j].ID == m.Course_ID) && (crssems.Any(m => m.Course.ID == courses[j].ID && m.Semester.Type == sems[k].Type && m.Semester.Year == sems[k].Year)))
constMaxPerSem.AddTerm(1, CourseAllocation[i, j, k]);
}
String sCourseSem = "maxCourseStudent." + i + 1 + "_Semester." + k + 1;
model.AddConstr(constMaxPerSem <= MAX_COURSES_PER_SEMESTER, sCourseSem);
}
//PREREQUISITES
//Constrains the students to take prerequisite courses prior to taking a course that needs the prerequisite
for (int j = 0; j < courses.Length; j++)
{
if (courses[j].Prerequisites.Any() && students[i].Courses.Contains(courses[j]) && !completed.Any(m => m.GaTechId == students[i].GaTechId && courses[j].ID == m.Course_ID))
{
foreach (var prereq in courses[j].Prerequisites)
{
int prereqIndex = Array.IndexOf(courses, prereq);
GRBLinExpr coursePrereqConst1 = 0.0;
GRBLinExpr coursePrereqConst2 = 0.0;
if (!completed.Any(m => m.GaTechId == students[i].GaTechId && m.Course.ID == prereq.ID))
{
for (int k = 0; k < sems.Length; k++)
{
if (prereqIndex >= 0)
{
coursePrereqConst1.AddTerm(k + 1, CourseAllocation[i, prereqIndex, k]);
coursePrereqConst2.AddTerm(k, CourseAllocation[i, j, k]);
}
}
}
model.AddConstr(coursePrereqConst1, GRB.LESS_EQUAL, coursePrereqConst2, "PREREQ_Student" + i + "_Course+" + j + "_Prereq" + prereqIndex);
}
}
}
}
//SENIORITY
//Students are already ordered from dB query by seniority in descending order and puts a preference to senior students over the next student that desires that
//same course with less seniority.
for (int j = 0; j < courses.Length; j++)
{
for (int i = 0; i < students.Length - 1; i++)
{
if (students[i].Courses.Contains(courses[j]) && !completed.Any(m => m.GaTechId == students[i].GaTechId && courses[j].ID == m.Course_ID))
{
int SemsRemain = (students[i].Courses.Count - students[i].Student.CompletedCourses.Count) / 2 + (students[i].Courses.Count - students[i].Student.CompletedCourses.Count) % 2;
for (int n = i + 1; n < students.Length; n++)
{
if (students[n].Courses.Contains(courses[j]) && !completed.Any(m => m.GaTechId == students[n].GaTechId && courses[j].ID == m.Course_ID))
{
GRBLinExpr seniority = 0.0;
for (int k = 0; k < sems.Length; k++)
{
if (crssems.Any(m => m.Course.ID == courses[j].ID && m.Semester.Type == sems[k].Type && m.Semester.Year == sems[k].Year))
{
if (k <= SemsRemain)
{
seniority.AddTerm(1.0, CourseAllocation[i, j, k]);
seniority.AddTerm(-1.0, CourseAllocation[n, j, k]);
}
else
{
seniority.AddTerm(-1.0, CourseAllocation[i, j, k]);
seniority.AddTerm(1.0, CourseAllocation[n, j, k]);
}
}
}
model.AddConstr(seniority, GRB.GREATER_EQUAL, 0, "Seniority for Student." + students[i] + "_Course." + courses[j]);
break;
}
}
}
}
}
//Add the slack variable for all semester & course offerings then constrain the maximum number of students
//to take a couse in a semester.
for (int k = 0; k < sems.Length; k++)
{
for (int j = 0; j < courses.Length; j++)
{
if (crssems.Any(m => m.Course.ID == courses[j].ID && m.Semester.Type == sems[k].Type && m.Semester.Year == sems[k].Year))
{
slacks[j, k] = model.AddVar(0, GRB.INFINITY, 0, GRB.INTEGER, sems[k].Type.ToString() + "." + sems[k].Year.ToString() + "." + courses[j].Name + ".Slacks");
GRBLinExpr constMaxStudCrsSem = 0.0;
for (int i = 0; i < students.Length; i++)
{
if (!completed.Any(m => m.GaTechId == students[i].GaTechId && courses[j].ID == m.Course_ID))
constMaxStudCrsSem.AddTerm(1.0, CourseAllocation[i, j, k]);
}
model.Update();
constMaxStudCrsSem.AddTerm(-1.0, slacks[j, k]);
model.AddConstr(constMaxStudCrsSem <= crssems.Single(m => m.Course.ID == courses[j].ID && m.Semester.Type == sems[k].Type && m.Semester.Year == sems[k].Year).StudentLimit, sems[k].Type.ToString() + "." + sems[k].Year.ToString() + "." + courses[j].Name);
}
}
}
//Add total slack to the optimization model for all courses in the semesters they are offered.
GRBVar totSlack = model.AddVar(0, GRB.INFINITY, 0, GRB.INTEGER, "totSlack");
GRBLinExpr lhs = new GRBLinExpr();
lhs.AddTerm(-1.0, totSlack);
for (int j = 0; j < courses.Length; j++)
{
for (int k = 0; k < sems.Length; k++)
{
if (crssems.Any(m => m.Course.ID == courses[j].ID && m.Semester.Type == sems[k].Type && m.Semester.Year == sems[k].Year))
lhs.AddTerm(1.0, slacks[j, k]);
}
}
model.Update();
model.AddConstr(lhs, GRB.EQUAL, 0, "totSlack");
// Objective: minimize the total slack
GRBLinExpr obj = new GRBLinExpr();
obj.AddTerm(1.0, totSlack);
model.SetObjective(obj);
//Optimize the model to minimize the total slack and maximize students to course offerings based on input variables and constraints.
model.Optimize();
//Write Results optimization results to database
writeResults(CourseAllocation, students, courses, sems, crssems, dbConn, Convert.ToInt32(model.Get(GRB.DoubleAttr.ObjVal)), RunName);
//Clean-Up
model.Dispose();
env.Dispose();
}
catch (Exception e)
{
return Request.CreateErrorResponse(HttpStatusCode.InternalServerError, "An Error occured while running the optimization.");
}
}
return Request.CreateResponse(HttpStatusCode.OK);
}
static void Main()
{
try {
GRBEnv env = new GRBEnv("qp.log");
GRBModel model = new GRBModel(env);
// Create variables
GRBVar x = model.AddVar(0.0, 1.0, 0.0, GRB.CONTINUOUS, "x");
GRBVar y = model.AddVar(0.0, 1.0, 0.0, GRB.CONTINUOUS, "y");
GRBVar z = model.AddVar(0.0, 1.0, 0.0, GRB.CONTINUOUS, "z");
// Integrate new variables
model.Update();
// Set objective
GRBQuadExpr obj = x*x + x*y + y*y + y*z + z*z;
model.SetObjective(obj);
// Add constraint: x + 2 y + 3 z >= 4
model.AddConstr(x + 2 * y + 3 * z >= 4.0, "c0");
// Add constraint: x + y >= 1
model.AddConstr(x + y >= 1.0, "c1");
// Optimize model
model.Optimize();
Console.WriteLine(x.Get(GRB.StringAttr.VarName)
+ " " + x.Get(GRB.DoubleAttr.X));
Console.WriteLine(y.Get(GRB.StringAttr.VarName)
+ " " + y.Get(GRB.DoubleAttr.X));
Console.WriteLine(z.Get(GRB.StringAttr.VarName)
+ " " + z.Get(GRB.DoubleAttr.X));
Console.WriteLine("Obj: " + model.Get(GRB.DoubleAttr.ObjVal) + " " +
obj.Value);
// Change variable types to integer
x.Set(GRB.CharAttr.VType, GRB.INTEGER);
y.Set(GRB.CharAttr.VType, GRB.INTEGER);
z.Set(GRB.CharAttr.VType, GRB.INTEGER);
// Optimize model
model.Optimize();
Console.WriteLine(x.Get(GRB.StringAttr.VarName)
+ " " + x.Get(GRB.DoubleAttr.X));
Console.WriteLine(y.Get(GRB.StringAttr.VarName)
+ " " + y.Get(GRB.DoubleAttr.X));
Console.WriteLine(z.Get(GRB.StringAttr.VarName)
+ " " + z.Get(GRB.DoubleAttr.X));
Console.WriteLine("Obj: " + model.Get(GRB.DoubleAttr.ObjVal) + " " +
obj.Value);
// Dispose of model and env
model.Dispose();
env.Dispose();
} catch (GRBException e) {
Console.WriteLine("Error code: " + e.ErrorCode + ". " + e.Message);
}
}
public void RangeSetup(GRBModel model, double lb, INumExpr expr, double ub, string name)
{
this.model = model;
this.LB = lb;
this.UB = ub;
this._name = name;
if (expr == null)
{
_expr = new INumExpr();
}
else
{
_expr = expr;
}
this.constr = null;
if (lb > -System.Double.MaxValue && ub < System.Double.MaxValue)
{
// "lb < expr < ub" --> " expr - newvar = lb, 0 < newvar < ub - lb"
GRBVar var = model.AddVar(0, ub - lb, 0, GRB.CONTINUOUS, null);
GRBLinExpr modExpr = Expr.expr - var;
this.constr = model.AddConstr(modExpr, GRB.EQUAL, lb, name);
}
else if (lb > -System.Double.MaxValue)
{
this.constr = model.AddConstr(Expr.expr, GRB.GREATER_EQUAL, lb, name);
}
else
{
this.constr = model.AddConstr(Expr.expr, GRB.LESS_EQUAL, ub, name);
}
}
static void Main(string[] args)
{
int n = 9;
int s = 3;
if (args.Length < 1) {
Console.Out.WriteLine("Usage: sudoku_cs filename");
return;
}
try {
GRBEnv env = new GRBEnv();
GRBModel model = new GRBModel(env);
// Create 3-D array of model variables
GRBVar[,,] vars = new GRBVar[n,n,n];
for (int i = 0; i < n; i++) {
for (int j = 0; j < n; j++) {
for (int v = 0; v < n; v++) {
string st = "G_" + i.ToString() + "_" + j.ToString()
+ "_" + v.ToString();
vars[i,j,v] = model.AddVar(0.0, 1.0, 0.0, GRB.BINARY, st);
}
}
}
// Integrate variables into model
model.Update();
// Add constraints
GRBLinExpr expr;
// Each cell must take one value
for (int i = 0; i < n; i++) {
for (int j = 0; j < n; j++) {
expr = 0.0;
for (int v = 0; v < n; v++)
expr += vars[i,j,v];
string st = "V_" + i.ToString() + "_" + j.ToString();
model.AddConstr(expr == 1.0, st);
}
}
// Each value appears once per row
for (int i = 0; i < n; i++) {
for (int v = 0; v < n; v++) {
expr = 0.0;
for (int j = 0; j < n; j++)
expr += vars[i,j,v];
string st = "R_" + i.ToString() + "_" + v.ToString();
model.AddConstr(expr == 1.0, st);
}
}
// Each value appears once per column
for (int j = 0; j < n; j++) {
for (int v = 0; v < n; v++) {
expr = 0.0;
for (int i = 0; i < n; i++)
expr += vars[i,j,v];
string st = "C_" + j.ToString() + "_" + v.ToString();
model.AddConstr(expr == 1.0, st);
}
}
// Each value appears once per sub-grid
for (int v = 0; v < n; v++) {
for (int i0 = 0; i0 < s; i0++) {
for (int j0 = 0; j0 < s; j0++) {
expr = 0.0;
for (int i1 = 0; i1 < s; i1++) {
for (int j1 = 0; j1 < s; j1++) {
expr += vars[i0*s+i1,j0*s+j1,v];
}
}
string st = "Sub_" + v.ToString() + "_" + i0.ToString()
+ "_" + j0.ToString();
model.AddConstr(expr == 1.0, st);
}
}
}
// Update model
model.Update();
// Fix variables associated with pre-specified cells
StreamReader sr = File.OpenText(args[0]);
for (int i = 0; i < n; i++) {
string input = sr.ReadLine();
for (int j = 0; j < n; j++) {
int val = (int) input[j] - 48 - 1; // 0-based
if (val >= 0)
vars[i,j,val].Set(GRB.DoubleAttr.LB, 1.0);
}
}
// Optimize model
model.Optimize();
// Write model to file
model.Write("sudoku.lp");
double[,,] x = model.Get(GRB.DoubleAttr.X, vars);
Console.WriteLine();
for (int i = 0; i < n; i++) {
for (int j = 0; j < n; j++) {
for (int v = 0; v < n; v++) {
if (x[i,j,v] > 0.5) {
Console.Write(v+1);
}
}
}
Console.WriteLine();
}
// Dispose of model and env
model.Dispose();
env.Dispose();
} catch (GRBException e) {
Console.WriteLine("Error code: " + e.ErrorCode + ". " + e.Message);
}
}