public static void Main(String[] args)
{
try {
GRBEnv env = new GRBEnv();
double[] c = new double[] {1, 1, 0};
double[,] Q = new double[,] {{1, 1, 0}, {0, 1, 1}, {0, 0, 1}};
double[,] A = new double[,] {{1, 2, 3}, {1, 1, 0}};
char[] sense = new char[] {'>', '>'};
double[] rhs = new double[] {4, 1};
double[] lb = new double[] {0, 0, 0};
bool success;
double[] sol = new double[3];
success = dense_optimize(env, 2, 3, c, Q, A, sense, rhs,
lb, null, null, sol);
if (success) {
Console.WriteLine("x: " + sol[0] + ", y: " + sol[1] + ", z: " + sol[2]);
}
// Dispose of environment
env.Dispose();
} catch (GRBException e) {
Console.WriteLine("Error code: " + e.ErrorCode + ". " + e.Message);
}
}
public Cplex()
{
this._env = new GRBEnv("gurobi.log");
this._model = new GRBModel(_env);
_model.GetEnv().Set(GRB.IntParam.UpdateMode, 1);
this._status = 0;
}
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(string[] args)
{
if (args.Length < 1)
{
Console.Out.WriteLine("Usage: lpmethod_cs filename");
return;
}
try {
// Read model
GRBEnv env = new GRBEnv();
GRBModel model = new GRBModel(env, args[0]);
GRBEnv menv = model.GetEnv();
// Solve the model with different values of Method
int bestMethod = -1;
double bestTime = menv.Get(GRB.DoubleParam.TimeLimit);
for (int i = 0; i <= 2; ++i)
{
model.Reset();
menv.Set(GRB.IntParam.Method, i);
model.Optimize();
if (model.Get(GRB.IntAttr.Status) == GRB.Status.OPTIMAL)
{
bestTime = model.Get(GRB.DoubleAttr.Runtime);
bestMethod = i;
// Reduce the TimeLimit parameter to save time
// with other methods
menv.Set(GRB.DoubleParam.TimeLimit, bestTime);
}
}
// Report which method was fastest
if (bestMethod == -1)
{
Console.WriteLine("Unable to solve this model");
}
else
{
Console.WriteLine("Solved in " + bestTime
+ " seconds with Method: " + bestMethod);
}
// 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 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();
}
/// <summary>Set-up the environment for batch mode optimization.
/// </summary>
/// <remarks>
/// The fuction creates an empty environment, sets all neccessary
/// parameters, and returns the ready-to-be-started Env object to
/// caller.
/// </remarks>
static GRBEnv setupbatchenv()
{
GRBEnv env = new GRBEnv(true);
env.CSBatchMode = 1;
env.CSManager = "http://localhost:61080";
env.LogFile = "batchmode.log";
env.ServerPassword = "******";
env.UserName = "******";
// No network communication happened up to this point. This will happen
// once the caller invokes the start() method of the returned Env object.
return(env);
}
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(string[] args)
{
if (args.Length < 1)
{
Console.Out.WriteLine("Usage: params_cs filename");
return;
}
try {
// Read model and verify that it is a MIP
GRBEnv env = new GRBEnv();
GRBModel m = new GRBModel(env, args[0]);
if (m.IsMIP == 0)
{
Console.WriteLine("The model is not an integer program");
Environment.Exit(1);
}
// Set a 5 second time limit
m.Parameters.TimeLimit = 5.0;
// Now solve the model with different values of MIPFocus
GRBModel bestModel = new GRBModel(m);
bestModel.Optimize();
for (int i = 1; i <= 3; ++i)
{
m.Reset();
m.Parameters.MIPFocus = i;
m.Optimize();
if (bestModel.MIPGap > m.MIPGap)
{
GRBModel swap = bestModel;
bestModel = m;
m = swap;
}
}
// Finally, delete the extra model, reset the time limit and
// continue to solve the best model to optimality
m.Dispose();
bestModel.Parameters.TimeLimit = GRB.INFINITY;
bestModel.Optimize();
Console.WriteLine("Solved with MIPFocus: " +
bestModel.Parameters.MIPFocus);
} 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);
}
}
public void GenerateBaseModel(string datFilePath)
{
_constraintModel = DatFileParser.ParseDatFile(datFilePath);
ExampleName = new FileInfo(datFilePath).Name;
try
{
var path = @"C:\IJCAI\Output\TestRuns\Logs\";
if (!Directory.Exists(path))
{
Directory.CreateDirectory(path);
}
env = new GRBEnv(path + ExampleName + ".log")
{
LogToConsole = 0,
NodefileStart = 0.5
};
_model = new GRBModel(env);
_k = _constraintModel.K;
_b = _constraintModel.B;
// Optimization values
S = _model.AddVar(0.0, _k - 1, 0.0, GRB.CONTINUOUS, "S"); // Number of interrupted job pairs
L = _model.AddVar(0.0, _k - 1, 0.0, GRB.CONTINUOUS, "L"); // Longest time a cable resides in storage
M = _model.AddVar(0.0, _k - 1, 0.0, GRB.CONTINUOUS, "M"); // Maximum number of cables stored simultaneously
N = _model.AddVar(0.0, _k - 1, 0.0, GRB.CONTINUOUS, "N"); // Number of violated soft atomic constraints
pfc = CreatePermutationVariable();
// objective
var objExpr = new GRBQuadExpr();
objExpr.AddTerm(Math.Pow(_k, 3), S);
objExpr.AddTerm(Math.Pow(_k, 2), M);
objExpr.AddTerm(Math.Pow(_k, 1), L);
objExpr.AddTerm(Math.Pow(_k, 0), N);
_model.SetObjective(objExpr);
_model.Parameters.TimeLimit = 300; // 300 seconds
}
catch (Exception e)
{
Console.WriteLine(e.ToString());
}
}
///<summary>Instruct the cluster manager to discard all data relating
/// to this BatchID</summary>
static void batchdiscard(string batchID)
{
// Setup and start environment, create local Batch handle object
GRBEnv env = setupbatchenv();
env.Start();
GRBBatch batch = new GRBBatch(env, batchID);
// Remove batch request from manager
batch.Discard();
// Cleanup
batch.Dispose();
env.Dispose();
}
protected override Status Solve()
{
this.env = new GRBEnv();
this.model = new GRBModel(this.env);
this.SetModelParameters();
this.CreateVariables();
this.CreateConstraints();
this.CreateObjective();
this.SetInitStartTimes();
this.model.SetTimeLimit(this.RemainingTime);
this.model.Optimize();
return(this.model.GetResultStatus());
}
private void OptimizeFASub()
{
_env_FlowAssignmentSub = new GRBEnv("FASub.log");
_grbModel_FlowAssignmentSub = new GRBModel(_env_FlowAssignmentSub);
BuildVar_FA();
BuildObj_FA();
BuildConst_FA();
_grbModel_FlowAssignmentSub.Write("FASub.lp");
_grbModel_FlowAssignmentSub.Optimize();
OutputValue();
}
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 Main(string[] args)
{
if (args.Length < 1) {
Console.Out.WriteLine("Usage: lpmethod_cs filename");
return;
}
try {
// Read model
GRBEnv env = new GRBEnv();
GRBModel model = new GRBModel(env, args[0]);
GRBEnv menv = model.GetEnv();
// Solve the model with different values of Method
int bestMethod = -1;
double bestTime = menv.Get(GRB.DoubleParam.TimeLimit);
for (int i = 0; i <= 2; ++i)
{
model.Reset();
menv.Set(GRB.IntParam.Method, i);
model.Optimize();
if (model.Get(GRB.IntAttr.Status) == GRB.Status.OPTIMAL)
{
bestTime = model.Get(GRB.DoubleAttr.Runtime);
bestMethod = i;
// Reduce the TimeLimit parameter to save time
// with other methods
menv.Set(GRB.DoubleParam.TimeLimit, bestTime);
}
}
// Report which method was fastest
if (bestMethod == -1) {
Console.WriteLine("Unable to solve this model");
} else {
Console.WriteLine("Solved in " + bestTime
+ " seconds with Method: " + bestMethod);
}
// 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("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");
// 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.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);
}
}
static void Main(string[] args)
{
if (args.Length < 1)
{
Console.Out.WriteLine("Usage: params_cs filename");
return;
}
try {
// Read model and verify that it is a MIP
GRBEnv env = new GRBEnv();
GRBModel basemodel = new GRBModel(env, args[0]);
if (basemodel.Get(GRB.IntAttr.IsMIP) == 0)
{
Console.WriteLine("The model is not an integer program");
Environment.Exit(1);
}
// Set a 5 second time limit
basemodel.GetEnv().Set(GRB.DoubleParam.TimeLimit, 5);
// Now solve the model with different values of MIPFocus
double bestGap = GRB.INFINITY;
GRBModel bestModel = null;
for (int i = 0; i <= 3; ++i)
{
GRBModel m = new GRBModel(basemodel);
m.GetEnv().Set(GRB.IntParam.MIPFocus, i);
m.Optimize();
if (bestModel == null || bestGap > Gap(m))
{
bestModel = m;
bestGap = Gap(bestModel);
}
}
// Finally, reset the time limit and continue to solve the
// best model to optimality
bestModel.GetEnv().Set(GRB.DoubleParam.TimeLimit, GRB.INFINITY);
bestModel.Optimize();
Console.WriteLine("Solved with MIPFocus: " +
bestModel.GetEnv().Get(GRB.IntParam.MIPFocus));
} catch (GRBException e) {
Console.WriteLine("Error code: " + e.ErrorCode + ". " +
e.Message);
}
}
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());
}
///<summary>Final Report for Batch Request</summary>
static void printfinalreport(string batchID)
{
// Setup and start environment, create local Batch handle object
GRBEnv env = setupbatchenv();
env.Start();
GRBBatch batch = new GRBBatch(env, batchID);
switch (batch.BatchStatus)
{
case GRB.BatchStatus.CREATED:
Console.WriteLine("Batch status is 'CREATED'\n");
break;
case GRB.BatchStatus.SUBMITTED:
Console.WriteLine("Batch is 'SUBMITTED\n");
break;
case GRB.BatchStatus.ABORTED:
Console.WriteLine("Batch is 'ABORTED'\n");
break;
case GRB.BatchStatus.FAILED:
Console.WriteLine("Batch is 'FAILED'\n");
break;
case GRB.BatchStatus.COMPLETED:
Console.WriteLine("Batch is 'COMPLETED'\n");
// Get JSON solution as string
Console.WriteLine("JSON solution:" + batch.GetJSONSolution());
// Write the full JSON solution string to a file
batch.WriteJSONSolution("batch-sol.json.gz");
break;
default:
// Should not happen
Console.WriteLine("Unknown BatchStatus" + batch.BatchStatus);
Environment.Exit(1);
break;
}
// Cleanup
batch.Dispose();
env.Dispose();
}
///<summary>Wait for the final status of the batch. Initially the
/// status of a batch is <see cref="GRB.BatchStatus.SUBMITTED"/>;
/// the status will change once the batch has been processed
/// (by a compute server).</summary>
static void waitforfinalstatus(string batchID)
{
// Wait no longer than one hour
double maxwaittime = 3600;
DateTime start = DateTime.Now;
// Setup and start environment, create local Batch handle object
GRBEnv env = setupbatchenv();
env.Start();
GRBBatch batch = new GRBBatch(env, batchID);
try {
while (batch.BatchStatus == GRB.BatchStatus.SUBMITTED)
{
// Abort this batch if it is taking too long
TimeSpan interval = DateTime.Now - start;
if (interval.TotalSeconds > maxwaittime)
{
batch.Abort();
break;
}
// Wait for two seconds
System.Threading.Thread.Sleep(2000);
// Update the resident attribute cache of the Batch object
// with the latest values from the cluster manager.
batch.Update();
// If the batch failed, we retry it
if (batch.BatchStatus == GRB.BatchStatus.FAILED)
{
batch.Retry();
System.Threading.Thread.Sleep(2000);
batch.Update();
}
}
} finally {
// Print information about error status of the job
// that processed the batch
printbatcherrorinfo(ref batch);
batch.Dispose();
env.Dispose();
}
}
private void OptimizeSchemeSub()
{
_env_SchemeGenerateSub = new GRBEnv("SchemeSub.log");
_grbModel_SchemeGenerateSub = new GRBModel(_env_SchemeGenerateSub);
BuildVar_SG();
BuildObj_SG();
BuildConst_SG();
_grbModel_SchemeGenerateSub.Write("SchemeSub.lp");
_grbModel_SchemeGenerateSub.Optimize();
OutputSolution_SchemeSub();
//_grbModel_SchemeGenerateSub.Dispose();
//_env_SchemeGenerateSub.Dispose();
}
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);
}
}
public LinearModel(SolverType type, Action <string> logger, int threadCount = 0)
{
Type = type;
_logger = logger;
switch (type)
{
case SolverType.CPLEX:
{
CplexModel = new Cplex();
_cplexStatusCallback = new CplexStatusCallback(this)
{
};
CplexModel.SetOut(new CplexOutputHandler(logger));
CplexModel.Use(_cplexStatusCallback);
if (threadCount > 0)
{
CplexModel.SetParam(Cplex.IntParam.Threads, threadCount);
}
}
break;
case SolverType.Gurobi:
{
GRBEnv gurobiEnvironment = new GRBEnv();
GurobiModel = new GRBModel(gurobiEnvironment);
GurobiModel.GetEnv().Set(GRB.IntParam.UpdateMode, 1); // Enable immediate updates to better support the lazy initialization of the wrappers (at minor performance and memory costs)
GurobiModel.GetEnv().Set(GRB.IntParam.OutputFlag, 0);
if (threadCount > 0)
{
GurobiModel.GetEnv().Set(GRB.IntParam.Threads, threadCount);
}
_gurobiStatusCallback = new GurobiStatusCallback(this)
{
Logger = logger
};
GurobiModel.SetCallback(_gurobiStatusCallback);
}
break;
default: throw new ArgumentException("Unknown solver type: " + Type);
}
}
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();
}
static void Main(string[] args)
{
if (args.Length < 1)
{
Console.Out.WriteLine("Usage: tune_cs filename");
return;
}
try {
GRBEnv env = new GRBEnv();
// Read model from file
GRBModel model = new GRBModel(env, args[0]);
// Set the TuneResults parameter to 1
model.GetEnv().Set(GRB.IntParam.TuneResults, 1);
// Tune the model
model.Tune();
// Get the number of tuning results
int resultcount = model.Get(GRB.IntAttr.TuneResultCount);
if (resultcount > 0)
{
// Load the tuned parameters into the model's environment
model.GetTuneResult(0);
// Write the tuned parameters to a file
model.Write("tune.prm");
// Solve the model using the tuned parameters
model.Optimize();
}
// Dispose of model and environment
model.Dispose();
env.Dispose();
} catch (GRBException e) {
Console.WriteLine("Error code: " + e.ErrorCode + ". " + e.Message);
}
}
public ProblemOutput Solve(ProblemInput problem)
{
try {
GRBEnv env = new GRBEnv();
double[] lb = ArrayHelper.CreateArray <double>(problem.Linear.Length);
double[] sol = ArrayHelper.CreateArray <double>(problem.Linear.Length);
double val = 0.0;
var success = GurobiSolve(env, problem.ConstraintMatrix.GetLength(0), problem.ConstraintMatrix.GetLength(1), problem.Linear, problem.Quadratic, problem.ConstraintMatrix, problem.ConstraintValues, lb, null, null, sol, ref val);
var solution = new ProblemOutput
{
HasSolution = success,
Value = success ? val : double.NaN,
Solution = success ? sol : Enumerable.Repeat(double.NaN, problem.N).ToArray()
};
// Dispose of environment
env.Dispose();
return(solution);
} catch (GRBException e) {
return(null);
}
}
public void Optimize()
{
Data.LoadData();
GenerateInitialFeasibleSolution();
while (true)
{
_envMaster = new GRBEnv("CG_Model.log");
_grbModelMaster = new GRBModel(_envMaster);
BuildVar();
GenerateConst();
_grbModelMaster.Write("CG_Model.lp");
_grbModelMaster.Optimize();
GetDual();
OutputSolution();
OptimizeSchemeSub();
OptimizeFASub();
bool IsActive = AddColumn();
_grbModelMaster.Dispose();
_envMaster.Dispose();
_grbModel_SchemeGenerateSub.Dispose();
_env_SchemeGenerateSub.Dispose();
_grbModel_FlowAssignmentSub.Dispose();
_env_FlowAssignmentSub.Dispose();
if (!IsActive)
{
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);
}
private GRBVar[,] _x; // starting time of job j on machine a
#endregion Fields
#region Constructors
public GurobiJspModel(ProblemInstance prob, string name, int tmlim_min)
{
_n = prob.NumJobs;
_m = prob.NumMachines;
Info = "Starting gurobi optimisation";
_fileName = String.Format("jssp.{0}.log", name);
// Model
try
{
_env = new GRBEnv(_fileName);
if (tmlim_min > 0)
_env.Set(GRB.DoubleParam.TimeLimit, tmlim_min*60); // time limit is set to seconds!
_env.Set(GRB.IntParam.LogToConsole, 0);
_model = new GRBModel(_env);
_model.Set(GRB.StringAttr.ModelName, "jsp");
}
catch (GRBException e)
{
Console.WriteLine("Error code: " + e.ErrorCode + ". " + e.Message);
}
DecisionVariables();
ProcessingOrder(prob.Procs, prob.Sigma);
DisjunctiveCondition(prob.Procs);
Objective(prob.Procs, prob.Sigma);
//TrueOptimumDecVars = Optimise(out TrueOptimum);
//if (TrueOptimum > 0) // Objective cutoff
// _model.GetEnv().Set(GRB.DoubleParam.Cutoff, TrueOptimum + 0.5);
/* Indicates that you aren't interested in solutions whose objective values
* are worse than the specified value. If the objective value for the optimal
* solution is better than the specified cutoff, the solver will return the
* optimal solution. Otherwise, it will terminate with a CUTOFF status.
*/
// seems to be only for LP relaxation, not MIP objective
}
static void Main(string[] args)
{
HashSet <string> nodes_set = new HashSet <string>();
List <Arc> arcs = new List <Arc>();
StreamReader stream = new StreamReader("shortest_path.txt");
ReadNetwork(stream, nodes_set, arcs);
GRBEnv env = new GRBEnv();
SolvePrimal(env, nodes_set, arcs);
Console.WriteLine("primal solved");
try
{
SolveDual3(env, nodes_set, arcs);
env.Dispose();
}
catch (GRBException e)
{
Console.WriteLine(e.ErrorCode);
throw e;
}
}
static void Main(string[] args)
{
if (args.Length < 1)
{
Console.Out.WriteLine("Usage: callback_cs filename");
return;
}
try {
GRBEnv env = new GRBEnv();
GRBModel model = new GRBModel(env, args[0]);
GRBVar[] vars = model.GetVars();
// Create a callback object and associate it with the model
model.SetCallback(new callback_cs(vars));
model.Optimize();
double[] x = model.Get(GRB.DoubleAttr.X, vars);
string[] vnames = model.Get(GRB.StringAttr.VarName, vars);
for (int j = 0; j < vars.Length; j++)
{
if (x[j] != 0.0)
{
Console.WriteLine(vnames[j] + " " + x[j]);
}
}
// Dispose of model and env
model.Dispose();
env.Dispose();
} catch (GRBException e) {
Console.WriteLine("Error code: " + e.ErrorCode + ". " + e.Message);
Console.WriteLine(e.StackTrace);
}
}
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());
}
///<summary>Create a batch request for given problem file</summary>
static string newbatchrequest(string filename)
{
string batchID = "";
// Start environment, create Model object from file
GRBEnv env = setupbatchenv();
env.Start();
GRBModel model = new GRBModel(env, filename);
try {
// Set some parameters
model.Set(GRB.DoubleParam.MIPGap, 0.01);
model.Set(GRB.IntParam.JSONSolDetail, 1);
// Define tags for some variables to access their values later
int count = 0;
foreach (GRBVar v in model.GetVars())
{
v.VTag = "Variable" + count;
count += 1;
if (count >= 10)
{
break;
}
}
// Submit batch request
batchID = model.OptimizeBatch();
// Dispose of model and env
} finally {
model.Dispose();
env.Dispose();
}
return(batchID);
}
static void Main()
{
try {
// Create environment
GRBEnv env = new GRBEnv();
// Create a new m
GRBModel m = new GRBModel(env);
double lb = 0.0, ub = GRB.INFINITY;
GRBVar x = m.AddVar(lb, ub, 0.0, GRB.CONTINUOUS, "x");
GRBVar y = m.AddVar(lb, ub, 0.0, GRB.CONTINUOUS, "y");
GRBVar u = m.AddVar(lb, ub, 0.0, GRB.CONTINUOUS, "u");
GRBVar v = m.AddVar(lb, ub, 0.0, GRB.CONTINUOUS, "v");
// Set objective
m.SetObjective(2 * x + y, GRB.MAXIMIZE);
// Add linear constraint
m.AddConstr(u + 4 * v <= 9, "l1");
// Approach 1) PWL constraint approach
double intv = 1e-3;
double xmax = Math.Log(9.0);
int len = (int)Math.Ceiling(xmax / intv) + 1;
double[] xpts = new double[len];
double[] upts = new double[len];
for (int i = 0; i < len; i++)
{
xpts[i] = i * intv;
upts[i] = f(i * intv);
}
GRBGenConstr gc1 = m.AddGenConstrPWL(x, u, xpts, upts, "gc1");
double ymax = (9.0 / 4.0) * (9.0 / 4.0);
len = (int)Math.Ceiling(ymax / intv) + 1;
double[] ypts = new double[len];
double[] vpts = new double[len];
for (int i = 0; i < len; i++)
{
ypts[i] = i * intv;
vpts[i] = g(i * intv);
}
GRBGenConstr gc2 = m.AddGenConstrPWL(y, v, ypts, vpts, "gc2");
// Optimize the model and print solution
m.Optimize();
printsol(m, x, y, u, v);
// Approach 2) General function constraint approach with auto PWL
// translation by Gurobi
// restore unsolved state and get rid of PWL constraints
m.Reset();
m.Remove(gc1);
m.Remove(gc2);
m.Update();
GRBGenConstr gcf1 = m.AddGenConstrExp(x, u, "gcf1", "");
GRBGenConstr gcf2 = m.AddGenConstrPow(y, v, 0.5, "gcf2", "");
m.Parameters.FuncPieceLength = 1e-3;
// Optimize the model and print solution
m.Optimize();
printsol(m, x, y, u, v);
// Zoom in, use optimal solution to reduce the ranges and use a smaller
// pclen=1e-5 to solve it
x.LB = Math.Max(x.LB, x.X - 0.01);
x.UB = Math.Min(x.UB, x.X + 0.01);
y.LB = Math.Max(y.LB, y.X - 0.01);
y.UB = Math.Min(y.UB, y.X + 0.01);
m.Update();
m.Reset();
m.Parameters.FuncPieceLength = 1e-5;
// Optimize the model and print solution
m.Optimize();
printsol(m, x, y, u, v);
// Dispose of model and environment
m.Dispose();
env.Dispose();
} catch (GRBException e) {
Console.WriteLine("Error code: " + e.ErrorCode + ". " + e.Message);
}
}
/// <summary>
/// Adds the Gurobi OPF model for the provided power system, to the provided gurobi model.
/// </summary>
/// <param name="powerSystem"></param>
/// <param name="env"></param>
/// <param name="model"></param>
public OPFModel(IPowerSystem powerSystem, GRBEnv env, GRBModel model)
: base(env,model)
{
this.MyPowerSystem = powerSystem;
}
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);
}
}
public OPFModelForLDC(IPowerSystem powerSystem, GRBEnv env, GRBModel model, LoadBlock loadBlock)
: base(powerSystem, env, model)
{
this.LoadBlock = loadBlock;
}
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 {
// 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);
}
}
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 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 {
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(string[] args)
{
if (args.Length < 1) {
Console.Out.WriteLine("Usage: callback_cs filename");
return;
}
try {
GRBEnv env = new GRBEnv();
GRBModel model = new GRBModel(env, args[0]);
GRBVar[] vars = model.GetVars();
model.SetCallback(new callback_cs(vars));
model.Optimize();
double[] x = model.Get(GRB.DoubleAttr.X, vars);
string[] vnames = model.Get(GRB.StringAttr.VarName, vars);
for (int j = 0; j < vars.Length; j++) {
if (x[j] != 0.0) Console.WriteLine(vnames[j] + " " + x[j]);
}
for (int j = 0; j < vars.Length; j++) {
if (x[j] != 0.0) Console.WriteLine(vnames[j] + " " + x[j]);
}
// Dispose of model and env
model.Dispose();
env.Dispose();
} catch (GRBException e) {
Console.WriteLine("Error code: " + e.ErrorCode + ". " + e.Message);
Console.WriteLine(e.StackTrace);
}
}
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 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(string[] args)
{
if (args.Length < 1) {
Console.Out.WriteLine("Usage: mip2_cs filename");
return;
}
try {
GRBEnv env = new GRBEnv();
GRBModel model = new GRBModel(env, args[0]);
if (model.Get(GRB.IntAttr.IsMIP) == 0) {
Console.WriteLine("Model is not a MIP");
return;
}
model.Optimize();
int optimstatus = model.Get(GRB.IntAttr.Status);
double objval = 0;
if (optimstatus == GRB.Status.OPTIMAL) {
objval = model.Get(GRB.DoubleAttr.ObjVal);
Console.WriteLine("Optimal objective: " + objval);
} else if (optimstatus == GRB.Status.INF_OR_UNBD) {
Console.WriteLine("Model is infeasible or unbounded");
return;
} else if (optimstatus == GRB.Status.INFEASIBLE) {
Console.WriteLine("Model is infeasible");
return;
} else if (optimstatus == GRB.Status.UNBOUNDED) {
Console.WriteLine("Model is unbounded");
return;
} else {
Console.WriteLine("Optimization was stopped with status = "
+ optimstatus);
return;
}
/* Iterate over the solutions and compute the objectives */
GRBVar[] vars = model.GetVars();
model.GetEnv().Set(GRB.IntParam.OutputFlag, 0);
Console.WriteLine();
for (int k = 0; k < model.Get(GRB.IntAttr.SolCount); ++k) {
model.GetEnv().Set(GRB.IntParam.SolutionNumber, k);
double objn = 0.0;
for (int j = 0; j < vars.Length; j++) {
objn += vars[j].Get(GRB.DoubleAttr.Obj)
* vars[j].Get(GRB.DoubleAttr.Xn);
}
Console.WriteLine("Solution " + k + " has objective: " + objn);
}
Console.WriteLine();
model.GetEnv().Set(GRB.IntParam.OutputFlag, 1);
/* Create a fixed model, turn off presolve and solve */
GRBModel fixedmodel = model.FixedModel();
fixedmodel.GetEnv().Set(GRB.IntParam.Presolve, 0);
fixedmodel.Optimize();
int foptimstatus = fixedmodel.Get(GRB.IntAttr.Status);
if (foptimstatus != GRB.Status.OPTIMAL) {
Console.WriteLine("Error: fixed model isn't optimal");
return;
}
double fobjval = fixedmodel.Get(GRB.DoubleAttr.ObjVal);
if (Math.Abs(fobjval - objval) > 1.0e-6 * (1.0 + Math.Abs(objval))) {
Console.WriteLine("Error: objective values are different");
return;
}
GRBVar[] fvars = fixedmodel.GetVars();
double[] x = fixedmodel.Get(GRB.DoubleAttr.X, fvars);
string[] vnames = fixedmodel.Get(GRB.StringAttr.VarName, fvars);
for (int j = 0; j < fvars.Length; j++) {
if (x[j] != 0.0) Console.WriteLine(vnames[j] + " " + x[j]);
}
// Dispose of models and env
fixedmodel.Dispose();
model.Dispose();
env.Dispose();
} catch (GRBException e) {
Console.WriteLine("Error code: " + e.ErrorCode + ". " + e.Message);
}
}
/// <summary>
/// Create an instance of the object
/// </summary>
/// <param name="updateEventHandler">A method to call to handle an update event.</param>
public Engine(Action<ProcessUpdateEventArgs> updateEventHandler)
{
_updateEventHandler = updateEventHandler;
_env = new GRBEnv("ConferenceOptimizer.log");
_model = new GRBModel(_env);
}
private void SetupGurobiEnvironmentAndModel()
{
// Model
env = new GRBEnv();
model = new GRBModel(env);
model.Set(GRB.StringAttr.ModelName, "diet");
}
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(string[] args)
{
if (args.Length < 1)
{
Console.Out.WriteLine("Usage: lpmod_cs filename");
return;
}
try {
// Read model and determine whether it is an LP
GRBEnv env = new GRBEnv();
GRBModel model = new GRBModel(env, args[0]);
if (model.IsMIP != 0)
{
Console.WriteLine("The model is not a linear program");
Environment.Exit(1);
}
model.Optimize();
int status = model.Status;
if ((status == GRB.Status.INF_OR_UNBD) ||
(status == GRB.Status.INFEASIBLE) ||
(status == GRB.Status.UNBOUNDED))
{
Console.WriteLine("The model cannot be solved because it is "
+ "infeasible or unbounded");
Environment.Exit(1);
}
if (status != GRB.Status.OPTIMAL)
{
Console.WriteLine("Optimization was stopped with status " + status);
Environment.Exit(0);
}
// Find the smallest variable value
double minVal = GRB.INFINITY;
GRBVar minVar = null;
foreach (GRBVar v in model.GetVars())
{
double sol = v.X;
if ((sol > 0.0001) && (sol < minVal) && (v.LB == 0.0))
{
minVal = sol;
minVar = v;
}
}
Console.WriteLine("\n*** Setting " +
minVar.VarName + " from " + minVal +
" to zero ***\n");
minVar.UB = 0.0;
// Solve from this starting point
model.Optimize();
// Save iteration & time info
double warmCount = model.IterCount;
double warmTime = model.Runtime;
// Reset the model and resolve
Console.WriteLine("\n*** Resetting and solving "
+ "without an advanced start ***\n");
model.Reset();
model.Optimize();
double coldCount = model.IterCount;
double coldTime = model.Runtime;
Console.WriteLine("\n*** Warm start: " + warmCount + " iterations, " +
warmTime + " seconds");
Console.WriteLine("*** Cold start: " + coldCount + " iterations, " +
coldTime + " seconds");
// 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);
}
