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();
}
// 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);
}
/// <summary>
/// Exports the model to the specified path as an MPS-file.
/// </summary>
/// <param name="path">The path to the file (has to end with .mps).</param>
public void ExportMPS(string path)
{
path = path.EndsWith(".mps") ? path : path + ".mps";
switch (Type)
{
case SolverType.CPLEX: CplexModel.ExportModel(path); break;
case SolverType.Gurobi: GurobiModel.Update(); GurobiModel.Write(path); break;
default: throw new ArgumentException("Unknown solver type: " + Type);
}
}
static void SolveDual(GRBEnv env, HashSet <string> nodes_set, List <Arc> arcs)
{
GRBModel dual = new GRBModel(env);
Star forward_stars = new Star();
Star reverse_stars = new Star();
GetStars(nodes_set, arcs, forward_stars, reverse_stars);
Dictionary <Arc, GRBVar> arc_traversed = new Dictionary <Arc, GRBVar>();
foreach (Arc a in arcs)
{
arc_traversed[a] = dual.AddVar(0, 1, a.length, GRB.CONTINUOUS, "arc_traversed." + a.source + "." + a.dest);
}
dual.Update();
Dictionary <string, GRBConstr> flow_balance = new Dictionary <string, GRBConstr>();
foreach (string node in nodes_set)
{
GRBLinExpr lhs = new GRBLinExpr();
List <Arc> forward_star = forward_stars[node];
List <Arc> reverse_star = reverse_stars[node];
Console.WriteLine("node " + node);
Console.Write("Forward star: ");
foreach (Arc a in forward_star)
{
Console.Write(a.dest + ' ');
// lhs -= arc_traversed[a];
lhs.AddTerm(-1, arc_traversed[a]);
}
Console.Write("\nReverse star: ");
foreach (Arc a in reverse_star)
{
Console.Write(a.source + ' ');
lhs.AddTerm(1, arc_traversed[a]);
}
Console.WriteLine("");
flow_balance[node] = dual.AddConstr(lhs, '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();
foreach (var pair in arc_traversed)
{
Console.WriteLine("Arc {0}:{1} traversed = {2}", pair.Key.source, pair.Key.dest, pair.Value.Get(GRB.DoubleAttr.X));
}
Console.WriteLine("length of shortest path = " + dual.Get(GRB.DoubleAttr.ObjVal));
dual.Dispose();
}
private void CreateVariables(IEnumerable <MenuItem> items)
{
int n = items.Count();
var itemArray = items.ToArray();
_v = new GRBVar[n];
for (int i = 0; i < n; i++)
{
_v[i] = _model.AddVar(0.0, 8.0, 0.0, GRB.INTEGER, $"x[{i}]");
Console.WriteLine($"x[{i}] - {itemArray[i].Name}");
}
_model.Update();
}
public bool TrySolve(out double prepS, out double execS)
{
_model.SetObjective(_value);
_model.Parameters.DualReductions = 0;
_model.Update();
_model.Write("debug.lp");
_model.Optimize();
if (_model.Status != GRB.Status.OPTIMAL)
{
Logger.Warn($"Didn't find solution to time conditions. Gurobi status: {_model.Status}");
prepS = -1;
execS = -1;
return(false);
}
try
{
prepS = _prepS.X;
execS = _execS.X;
} catch
{
Logger.Warn($"Exception. Gurobi status: {_model.Status}");
prepS = -1;
execS = -1;
return(false);
}
return(true);
}
void BuildModel_Slave()
{
//决策变量
foreach (Node n in Data.NodeSet)
{
n.Result_IsServerLoacationSelected = _grbModel.AddVar(0.0, 1.0, 0.0, GRB.BINARY, "x_" + n.ID);
}
_grbModel.Update();
//目标函数
GRBLinExpr expr1 = 0;
foreach (Node n in Data.NodeSet)
{
expr1 += n.Result_IsServerLoacationSelected * Data.ServerInstalationFee;
}
GRBLinExpr expr2 = 0;
foreach (Node n in Data.NodeSet)
{
expr2 += Dual[n] * n.Result_IsServerLoacationSelected;
}
_grbModel.SetObjective(expr2 - expr1, GRB.MAXIMIZE);
}
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();
}
// This method will work irrespective of the size of the solution space
public ProductionTarget GetTargets(double claySupply, double glazeSupply)
{
GRBEnv env = new GRBEnv();
GRBModel model = new GRBModel(env);
GRBVar xS = CreateSmallVasesVariable(claySupply, model);
GRBVar xL = CreateLargeVasesVariable(glazeSupply, model);
model.Update();
// Create Constraints
CreateConstraints(model, xS, xL, claySupply, glazeSupply);
// Define Objective
model.SetObjective(3 * xS + 9 * xL, GRB.MAXIMIZE);
// Find the optimum
model.Optimize();
// Load the results
var results = model.Get(GRB.DoubleAttr.X, new GRBVar[] { xS, xL });
return(new Entities.ProductionTarget()
{
Small = Convert.ToInt32(results[0]), Large = Convert.ToInt32(results[1])
});
}
static void SolveDual3(GRBEnv env, HashSet <string> nodes_set, List <Arc> arcs)
{
GRBModel dual = new GRBModel(env);
Dictionary <string, GRBConstr> flow_balance = new Dictionary <string, GRBConstr>();
Dictionary <Arc, GRBVar> arc_traversed = new Dictionary <Arc, GRBVar>();
GRBConstr[] constrs = dual.AddConstrs(nodes_set.Count);
dual.Update();
int i = 0;
foreach (string s in nodes_set)
{
GRBConstr con = constrs[i];
con.Set(GRB.StringAttr.ConstrName, "flow_balance." + s);
con.Set(GRB.CharAttr.Sense, GRB.EQUAL);
flow_balance[s] = con;
++i;
}
flow_balance[ORIGIN].Set(GRB.DoubleAttr.RHS, -1);
flow_balance[DESTINATION].Set(GRB.DoubleAttr.RHS, 1);
foreach (Arc a in arcs)
{
GRBColumn col = new GRBColumn();
col.AddTerm(1, flow_balance[a.dest]);
col.AddTerm(-1, flow_balance[a.source]);
arc_traversed[a] = dual.AddVar(0, 1, a.length, GRB.CONTINUOUS, col, "arc_traversed." + a.source + "." + a.dest);
}
dual.Optimize();
dual.Write("dual3.lp");
dual.Write("dual3.sol");
dual.Dispose();
}
private void BuildVar_SG()
{
foreach (Node n in Data.NodeSet)
{
GRBVar y = _grbModel_SchemeGenerateSub.AddVar(0.0, 1.0, 0.0, GRB.BINARY, "y_" + n.ID);
}
_grbModel_SchemeGenerateSub.Update();
}
static void Main(string[] args)
{
if (args.Length < 1)
{
Console.Out.WriteLine("Usage: feasopt_cs filename");
return;
}
try {
GRBEnv env = new GRBEnv();
GRBModel feasmodel = new GRBModel(env, args[0]);
// Create a copy to use FeasRelax feature later */
GRBModel feasmodel1 = new GRBModel(feasmodel);
// Clear objective
feasmodel.SetObjective(new GRBLinExpr());
// Add slack variables
GRBConstr[] c = feasmodel.GetConstrs();
for (int i = 0; i < c.Length; ++i)
{
char sense = c[i].Get(GRB.CharAttr.Sense);
if (sense != '>')
{
GRBConstr[] constrs = new GRBConstr[] { c[i] };
double[] coeffs = new double[] { -1 };
feasmodel.AddVar(0.0, GRB.INFINITY, 1.0, GRB.CONTINUOUS, constrs,
coeffs, "ArtN_" + c[i].Get(GRB.StringAttr.ConstrName));
}
if (sense != '<')
{
GRBConstr[] constrs = new GRBConstr[] { c[i] };
double[] coeffs = new double[] { 1 };
feasmodel.AddVar(0.0, GRB.INFINITY, 1.0, GRB.CONTINUOUS, constrs,
coeffs, "ArtP_" +
c[i].Get(GRB.StringAttr.ConstrName));
}
}
feasmodel.Update();
// Optimize modified model
feasmodel.Write("feasopt.lp");
feasmodel.Optimize();
// Use FeasRelax feature */
feasmodel1.FeasRelax(GRB.FEASRELAX_LINEAR, true, false, true);
feasmodel1.Write("feasopt1.lp");
feasmodel1.Optimize();
// Dispose of model and env
feasmodel1.Dispose();
feasmodel.Dispose();
env.Dispose();
} catch (GRBException e) {
Console.WriteLine("Error code: " + e.ErrorCode + ". " + e.Message);
}
}
private void BuildVar()
{
foreach (Node n in Frmk.Data.NodeSet)
{
GRBVar x = _model.AddVar(0.0, 1.0, Frmk.Data.ServerInstalationFee, GRB.BINARY, "x_" + n.ID);
}
GRBVar z = _model.AddVar(0.0, GRB.INFINITY, 1.0, GRB.CONTINUOUS, "z");
_model.Update();
}
static void Main(string[] args)
{
if (args.Length < 1) {
Console.Out.WriteLine("Usage: feasopt_cs filename");
return;
}
try {
GRBEnv env = new GRBEnv();
GRBModel feasmodel = new GRBModel(env, args[0]);
// Create a copy to use FeasRelax feature later */
GRBModel feasmodel1 = new GRBModel(feasmodel);
// Clear objective
feasmodel.SetObjective(new GRBLinExpr());
// Add slack variables
GRBConstr[] c = feasmodel.GetConstrs();
for (int i = 0; i < c.Length; ++i) {
char sense = c[i].Get(GRB.CharAttr.Sense);
if (sense != '>') {
GRBConstr[] constrs = new GRBConstr[] { c[i] };
double[] coeffs = new double[] { -1 };
feasmodel.AddVar(0.0, GRB.INFINITY, 1.0, GRB.CONTINUOUS, constrs,
coeffs, "ArtN_" + c[i].Get(GRB.StringAttr.ConstrName));
}
if (sense != '<') {
GRBConstr[] constrs = new GRBConstr[] { c[i] };
double[] coeffs = new double[] { 1 };
feasmodel.AddVar(0.0, GRB.INFINITY, 1.0, GRB.CONTINUOUS, constrs,
coeffs, "ArtP_" +
c[i].Get(GRB.StringAttr.ConstrName));
}
}
feasmodel.Update();
// Optimize modified model
feasmodel.Write("feasopt.lp");
feasmodel.Optimize();
// Use FeasRelax feature */
feasmodel1.FeasRelax(GRB.FEASRELAX_LINEAR, true, false, true);
feasmodel1.Write("feasopt1.lp");
feasmodel1.Optimize();
// Dispose of model and env
feasmodel1.Dispose();
feasmodel.Dispose();
env.Dispose();
} catch (GRBException e) {
Console.WriteLine("Error code: " + e.ErrorCode + ". " + e.Message);
}
}
static void Main()
{
try {
GRBEnv env = new GRBEnv("qcp.log");
GRBModel model = new GRBModel(env);
// Create variables
GRBVar x = model.AddVar(0.0, GRB.INFINITY, 0.0, GRB.CONTINUOUS, "x");
GRBVar y = model.AddVar(0.0, GRB.INFINITY, 0.0, GRB.CONTINUOUS, "y");
GRBVar z = model.AddVar(0.0, GRB.INFINITY, 0.0, GRB.CONTINUOUS, "z");
// Integrate new variables
model.Update();
// Set objective
GRBLinExpr obj = x;
model.SetObjective(obj, GRB.MAXIMIZE);
// Add linear constraint: x + y + z = 1
model.AddConstr(x + y + z == 1.0, "c0");
// Add second-order cone: x^2 + y^2 <= z^2
model.AddQConstr(x * x + y * y <= z * z, "qc0");
// Add rotated cone: x^2 <= yz
model.AddQConstr(x * x <= y * z, "qc1");
// 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);
}
}
static void SolvePrimal(GRBEnv env, HashSet <string> nodes_set, List <Arc> arcs)
{
GRBModel m = new GRBModel(env);
Dictionary <string, GRBVar> distances = new Dictionary <string, GRBVar>(); // pi
foreach (string node in nodes_set)
{
distances[node] = m.AddVar(0, GRB.INFINITY, 0, GRB.CONTINUOUS, "distance." + node);
}
m.Update();
distances[ORIGIN].Set(GRB.DoubleAttr.Obj, -1);
distances[DESTINATION].Set(GRB.DoubleAttr.Obj, 1);
m.Set(GRB.IntAttr.ModelSense, -1);
Dictionary <Arc, GRBConstr> constrs = new Dictionary <Arc, GRBConstr>();
foreach (Arc a in arcs)
{
constrs[a] = m.AddConstr(distances[a.dest] <= distances[a.source] + a.length, "distance_con." + a.source + "." + a.dest);
}
m.Update();
m.Write("shortest_path.lp");
m.Optimize();
foreach (var pair in distances)
{
Console.WriteLine("distance to {0} is {1}", pair.Key, pair.Value.Get(GRB.DoubleAttr.X));
}
foreach (var pair in constrs)
{
GRBConstr con = pair.Value;
if (con.Get(GRB.DoubleAttr.Pi) > 0.5)
{
Console.WriteLine("Arc {0}, {1} is in shortest path", pair.Key.source, pair.Key.dest);
}
}
Console.WriteLine("Length of shortest path is {0}", m.Get(GRB.DoubleAttr.ObjVal));
m.Dispose();
}
private void BuildVar()
{
foreach (Scheme s in SchemeColumnPool)
{
_grbModelMaster.AddVar(0.0, 1.0, s.GetTotalInstallationFee(Data.ServerInstalationFee), GRB.CONTINUOUS, "lambda_" + s.ID);
}
foreach (ExtremePoint e in EPColumnPool)
{
_grbModelMaster.AddVar(0.0, 1.0, e.TotalCost, GRB.CONTINUOUS, "mu_" + e.ID);
}
_grbModelMaster.Update();
}
public override object CreateProblem(int columns)
{
NUM_COLS = columns;
GRBModel model = new GRBModel(env);
for (int i = 0; i < NUM_COLS; i++)
{
model.AddVar(Double.NegativeInfinity, Double.PositiveInfinity, 0.0, GRB.CONTINUOUS, "C" + i);
}
model.Update();
return(model);
}
public override bool DelColumn(object solver, int column)
{
GRBModel model = solver as GRBModel;
if (model == null)
{
return(false);
}
model.Remove(model.GetVars()[column]);
model.Update();
return(true);
}
public override bool DelConstraint(object solver, int row)
{
GRBModel model = solver as GRBModel;
if (model == null)
{
return(false);
}
model.Remove(model.GetConstrs()[row]);
model.Update();
return(true);
}
private void BuildVar_FA()
{
foreach (Arc a in Data.ArcSet)
{
GRBVar x = _grbModel_FlowAssignmentSub.AddVar(0.0, GRB.INFINITY, 0.0, GRB.CONTINUOUS, "x_" + a.FromNode.ID + "_" + a.ToNode.ID);
}
foreach (Node n in Data.NodeSet)
{
GRBVar g = _grbModel_FlowAssignmentSub.AddVar(0.0, GRB.INFINITY, 0.0, GRB.CONTINUOUS, "g_" + n.ID);
//GRBVar d = _grbModel_FlowAssignmentSub.AddVar(0.0, 1.0, 0.0, GRB.CONTINUOUS, "d_" + n.ID);
}
_grbModel_FlowAssignmentSub.Update();
}
private void GenerateModel()
{
environment = new GRBEnv("gurobi.log");
model = new GRBModel(environment);
GenerateVariables();
model.Update();
GenerateObj();
GenerateConst();
model.Write("model.lp");
}
private void BuildVar()
{
foreach (Node n in Frmk.Data.NodeSet)
{
GRBVar alpha = _model.AddVar(0.0, GRB.INFINITY, -Frmk.Data.M * Frmk.SlaveObj.x[n], GRB.CONTINUOUS, "alpha_" + n.ID);
GRBVar beta = _model.AddVar(-GRB.INFINITY, GRB.INFINITY, n.Demand, GRB.CONTINUOUS, "beta_" + n.ID);
}
foreach (Arc a in Frmk.Data.ArcSet)
{
GRBVar gamma = _model.AddVar(0.0, GRB.INFINITY, -a.Capacity, GRB.CONTINUOUS, "gamma_" + a.FromNode.ID + "_" + a.ToNode.ID);
}
_model.Update();
_model.ModelSense = GRB.MAXIMIZE;
}
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();
GRBModel model = new GRBModel(env);
// Create variables
double[] ub = { 1, 1, 2 };
double[] obj = { -2, -1, -1 };
string[] names = { "x0", "x1", "x2" };
GRBVar[] x = model.AddVars(null, ub, obj, null, names);
// Integrate new variables
model.Update();
// Add first SOS1: x0=0 or x1=0
GRBVar[] sosv1 = { x[0], x[1] };
double[] soswt1 = { 1, 2 };
model.AddSOS(sosv1, soswt1, GRB.SOS_TYPE1);
// Add second SOS1: x0=0 or x2=0
GRBVar[] sosv2 = { x[0], x[2] };
double[] soswt2 = { 1, 2 };
model.AddSOS(sosv2, soswt2, GRB.SOS_TYPE1);
// Optimize model
model.Optimize();
for (int i = 0; i < 3; i++)
{
Console.WriteLine(x[i].Get(GRB.StringAttr.VarName) + " "
+ x[i].Get(GRB.DoubleAttr.X));
}
// 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);
}
}
static void Main()
{
try {
GRBEnv env = new GRBEnv();
GRBModel model = new GRBModel(env);
// Create variables
double[] ub = {1, 1, 2};
double[] obj = {-2, -1, -1};
string[] names = {"x0", "x1", "x2"};
GRBVar[] x = model.AddVars(null, ub, obj, null, names);
// Integrate new variables
model.Update();
// Add first SOS1: x0=0 or x1=0
GRBVar[] sosv1 = {x[0], x[1]};
double[] soswt1 = {1, 2};
model.AddSOS(sosv1, soswt1, GRB.SOS_TYPE1);
// Add second SOS1: x0=0 or x2=0
GRBVar[] sosv2 = {x[0], x[2]};
double[] soswt2 = {1, 2};
model.AddSOS(sosv2, soswt2, GRB.SOS_TYPE1);
// Optimize model
model.Optimize();
for (int i = 0; i < 3; i++)
Console.WriteLine(x[i].Get(GRB.StringAttr.VarName) + " "
+ x[i].Get(GRB.DoubleAttr.X));
// Dispose of model and env
model.Dispose();
env.Dispose();
} catch (GRBException e) {
Console.WriteLine("Error code: " + e.ErrorCode + ". " + e.Message);
}
}
private void CreateVariables(int sessionCount, int roomCount, int timeslotCount)
{
_v = new GRBVar[sessionCount, roomCount, timeslotCount];
for (int s = 0; s < sessionCount; s++)
{
for (int r = 0; r < roomCount; r++)
{
for (int t = 0; t < timeslotCount; t++)
{
_v[s, r, t] = _model.AddVar(0.0, 1.0, 0.0, GRB.BINARY, $"x[{s},{r},{t}]");
Console.WriteLine($"x[{s},{r},{t}]");
}
}
}
_s = new GRBVar[sessionCount];
for (int s = 0; s < sessionCount; s++)
{
_s[s] = _model.AddVar(0.0, Convert.ToDouble(timeslotCount), 0.0, GRB.INTEGER, $"s[{s}]");
Console.WriteLine($"s[{s}]");
}
_model.Update();
}
public void getOldList(GRBModel model, GRBConstr constr)
{
model.Update();
GRBLinExpr linExpr = model.GetRow(constr);
oldDict = new Dictionary<GRBVar, double>();
for (int i = 0; i < linExpr.Size; i++)
{
GRBVar var = linExpr.GetVar(i);
double val = linExpr.GetCoeff(i);
if (oldDict.ContainsKey(var))
{
oldDict[var] += val;
}
else
{
oldDict[var] = val;
}
}
constrs = new GRBConstr[1];
constrs[0] = constr;
}
public static void AddConstr(this GRBModel _m, GRBTempConstr _constr)
{
try
{
_m.AddConstr(_constr, null);
}
catch (GRBException _e)
{
switch (_e.ErrorCode)
{
case 10003:
_m.AddQConstr(_constr, null);
break;
case 20001:
_m.Update();
_m.AddConstr(_constr);
break;
}
}
}
void BuildModel_SubProblem1()
{
_env = new GRBEnv("SolutionLog.log");
_env.Set(GRB.DoubleParam.MIPGap, 0.0);
_env.Set(GRB.DoubleParam.TimeLimit, 500);
_grbModel = new GRBModel(_env);
//决策变量
foreach (Node n in Data.NodeSet)
{
n.Result_IsServerLoacationSelected = _grbModel.AddVar(0.0, 1.0, 0.0, GRB.BINARY, "x_" + n.ID);
}
_grbModel.Update();
//目标函数
GRBLinExpr expr1 = 0;
foreach (Node n in Data.NodeSet)
{
expr1 += n.Result_IsServerLoacationSelected * (Data.ServerInstalationFee - multiplier_p[n] * Data.M);
}
_grbModel.SetObjective(expr1, GRB.MINIMIZE);
}
public void BuildAndSolveDietLp()
{
DietLpProblem = new DietLpProblem();
SetupGurobiEnvironmentAndModel();
DietLpProblem.SetupDecisionVariables(model);
// The objective is to minimize the costs
model.Set(GRB.IntAttr.ModelSense, 1);
// Update model to integrate new variables
model.Update();
DietLpProblem.AddNutritionConstraints(model);
OptimizeAndPrintSolution();
AddLimitDiaryConstraint();
OptimizeAndPrintSolution();
DisposeModelAndEnvironment();
}
private void BuildMIPModel()
{
_env = new GRBEnv();
_model = new GRBModel(_env);
_varTimeslotUsed = new Dictionary <TimeSlot, GRBVar>();
foreach (var timeSlot in Data.TimeSlots)
{
_varTimeslotUsed[timeSlot] = _model.AddVar(0, 1, 1, GRB.BINARY, $"t_{timeSlot}");
}
_model.Update();
_model.AddConstr(Data.Rooms.Count * _varTimeslotUsed.Values.Sumx(), GRB.GREATER_EQUAL, Data.Courses.Sum(c => c.Lectures), "");
foreach (var roomCapacity in Data.RoomCapacities)
{
_model.AddConstr(Data.Rooms.Count(r => r.Capacity > roomCapacity.Value) * Data.TimeSlots.Count, GRB.GREATER_EQUAL,
Data.Courses.Where(c => c.NumberOfStudents > roomCapacity.Value).Sum(c => c.Lectures),
$"timecapcapcut_{roomCapacity.Value}");
}
//Consecutive timeslots
var timeslotlist = Data.TimeSlots.OrderBy(ts => ts.Period).ThenBy(ts => ts.Day).ToList();
for (var i = 0; i < timeslotlist.Count - 1; i++)
{
_model.AddConstr(_varTimeslotUsed[timeslotlist[i + 1]] - _varTimeslotUsed[timeslotlist[i]], GRB.LESS_EQUAL, 0,
$"timeslotconsec_{i}");
}
_model.SetCallback(new OutputCallback());
}
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);
}
}
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 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;
}
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 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(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);
}
}
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);
}
}
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);
}
}
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;
}
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);
}