public void Sequence() {
Solver solver = new Solver("Solver");
IntervalVar[] intervals =
solver.MakeFixedDurationIntervalVarArray(10, 0, 10, 5, false, "task");
DisjunctiveConstraint disjunctive = intervals.Disjunctive("Sequence");
SequenceVar var = disjunctive.SequenceVar();
Assignment ass = solver.MakeAssignment();
ass.Add(var);
ass.SetForwardSequence(var, new int[] { 1, 3, 5 });
int[] seq = ass.ForwardSequence(var);
Assert.Equal(3, seq.Length);
}
private static void Solve(int first_slot)
{
Console.WriteLine("----------------------------------------------------");
Solver solver = new Solver("SpeakerScheduling");
// the slots each speaker is available
int[][] speaker_availability =
{
new int[] { 1, 3, 4, 6, 7, 10, 12, 13, 14, 15, 16, 18, 19, 20, 21, 22, 23, 24, 25, 33, 34, 35, 36, 37, 38, 39, 40, 41, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59 },
new int[] { 1, 2, 7, 8, 10, 11, 16, 17, 18, 21, 22, 23, 24, 25, 33, 34, 35, 36, 37, 38, 39, 40, 42, 43, 44, 45, 46, 47, 48, 49, 52, 53, 54, 55, 56, 57, 58, 59,60 },
new int[] { 5, 6, 7, 10, 12, 14, 16, 17, 21, 22, 23, 24, 33, 35, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 51, 53, 55, 56, 57, 58,59 },
new int[] { 1, 2, 3, 4, 5, 6, 7, 11, 13, 14, 15, 16, 20, 24, 25, 33, 34, 35, 37, 38, 39, 40, 41, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 58, 59,60 },
new int[] { 4, 7, 8, 9, 16, 17, 19, 20, 21, 22, 23, 24, 25, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 49, 50, 51, 53, 55, 56, 57, 58, 59,60 },
new int[] { 4, 7, 9, 11, 12, 13, 14, 15, 16, 17, 18, 22, 23, 24, 33, 34, 35, 36, 38, 39, 42, 44, 46, 48, 49, 51, 53, 54, 55, 56,57 },
new int[] { 1, 2, 3, 4, 5, 6, 7, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 54, 55, 56, 57, 58, 59,60 },
new int[] { 1, 3, 11, 14, 15, 16, 17, 21, 22, 23, 24, 25, 33, 35, 36, 37, 39, 40, 41, 42, 43, 44, 45, 47, 48, 49, 51, 52, 53, 54, 55, 56, 57, 58, 59,60 },
new int[] { 1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 13, 18, 19, 20, 21, 22, 23, 24, 25, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 50, 51, 52, 53, 54, 55, 56, 57, 59,60 },
new int[] { 24, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 45, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59,60 },
new int[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 22, 23, 24, 25, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 50, 51, 52, 53,55, 56, 57, 58, 59, 60 },
new int[] { 3, 4, 5, 6, 13, 15, 16, 17, 18, 19, 21, 22, 24, 25, 33, 34, 35, 36, 37, 39, 40, 41, 42, 43, 44, 45, 47, 52, 53, 55, 57, 58, 59,60 },
new int[] { 4, 5, 6, 8, 11, 12, 13, 14, 17, 19, 20, 22, 23, 24, 25, 33, 34, 35, 36, 37, 39, 40, 41, 42, 43, 47, 48, 49, 50, 51, 52, 55, 56,57 },
new int[] { 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51,52, 53, 54, 55, 56, 57, 58, 59, 60 },
new int[] { 12, 25, 33, 35, 36, 37, 39, 41, 42, 43, 48, 51, 52, 53, 54, 57, 59,60 },
new int[] { 4, 8, 16, 17, 19, 23, 25, 33, 34, 35, 37, 41, 44, 45, 47, 48, 49,50 },
new int[] { 3, 23, 24, 25, 33, 35, 36, 37, 38, 39, 40, 42, 43, 44, 49, 50, 53, 54, 55, 56, 57, 58,60 },
new int[] { 7, 13, 19, 20, 22, 23, 24, 25, 33, 34, 35, 38, 40, 41, 42, 44, 45, 46, 47, 48, 49, 52, 53, 54, 58, 59, 60 }
};
// how long each talk lasts for each speaker
int[] durations = { 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1 };
int sum_of_durations = durations.Sum();
int number_of_speakers = durations.Length;
// calculate the total number of slots (maximum in the availability array)
// (and add the max durations)
int last_slot = (from s in Enumerable.Range(0, number_of_speakers)
select speaker_availability[s].Max()).Max();
Console.WriteLine(
"Scheduling {0} speakers, for a total of {1} slots, during [{2}..{3}]",
number_of_speakers, sum_of_durations, first_slot, last_slot);
// Start variable for all talks.
IntVar[] starts = new IntVar[number_of_speakers];
// We store the possible starts for all talks filtered from the
// duration and the speaker availability.
int[][] possible_starts = new int[number_of_speakers][];
for (int speaker = 0; speaker < number_of_speakers; ++speaker)
{
int duration = durations[speaker];
// Let's filter the possible starts.
List <int> filtered_starts = new List <int>();
int availability = speaker_availability[speaker].Length;
for (int index = 0; index < availability; ++index)
{
bool ok = true;
int slot = speaker_availability[speaker][index];
if (slot < first_slot)
{
continue;
}
for (int offset = 1; offset < durations[speaker]; ++offset)
{
if (index + offset >= availability ||
speaker_availability[speaker][index + offset] != slot + offset)
{
// discontinuity.
ok = false;
break;
}
}
if (ok)
{
filtered_starts.Add(slot);
}
possible_starts[speaker] = filtered_starts.ToArray();
}
starts[speaker] =
solver.MakeIntVar(possible_starts[speaker], "start[" + speaker + "]");
}
List <IntVar>[] contributions_per_slot =
new List <IntVar> [last_slot + 1];
for (int slot = first_slot; slot <= last_slot; ++slot)
{
contributions_per_slot[slot] = new List <IntVar>();
}
for (int speaker = 0; speaker < number_of_speakers; ++speaker)
{
int duration = durations[speaker];
IntVar start_var = starts[speaker];
foreach (int start in possible_starts[speaker])
{
for (int offset = 0; offset < duration; ++offset)
{
contributions_per_slot[start + offset].Add(start_var.IsEqual(start));
}
}
}
// Force the schedule to be consistent.
for (int slot = first_slot; slot <= last_slot; ++slot)
{
solver.Add(
solver.MakeSumLessOrEqual(contributions_per_slot[slot].ToArray(), 1));
}
// Add minimum start info.
for (int speaker = 0; speaker < number_of_speakers; ++speaker)
{
solver.Add(starts[speaker] >= first_slot);
}
// Creates makespan.
IntVar[] end_times = new IntVar[number_of_speakers];
for (int speaker = 0; speaker < number_of_speakers; speaker++)
{
end_times[speaker] = (starts[speaker] + (durations[speaker] - 1)).Var();
}
IntVar last_slot_var = end_times.Max().VarWithName("last_slot");
// Add trivial bound to objective.
last_slot_var.SetMin(first_slot + sum_of_durations - 1);
// Redundant scheduling constraint.
IntervalVar[] intervals =
solver.MakeFixedDurationIntervalVarArray(starts, durations, "intervals");
DisjunctiveConstraint disjunctive =
solver.MakeDisjunctiveConstraint(intervals, "disjunctive");
solver.Add(disjunctive);
//
// Search
//
List <IntVar> short_talks = new List <IntVar>();
List <IntVar> long_talks = new List <IntVar>();
for (int speaker = 0; speaker < number_of_speakers; ++speaker)
{
if (durations[speaker] == 1)
{
short_talks.Add(starts[speaker]);
}
else
{
long_talks.Add(starts[speaker]);
}
}
OptimizeVar objective_monitor = solver.MakeMinimize(last_slot_var, 1);
DecisionBuilder long_phase =
solver.MakePhase(long_talks.ToArray(),
Solver.CHOOSE_MIN_SIZE_LOWEST_MIN,
Solver.ASSIGN_MIN_VALUE);
DecisionBuilder short_phase =
new FlowAssign(short_talks.ToArray(), first_slot, last_slot_var);
DecisionBuilder obj_phase =
solver.MakePhase(last_slot_var,
Solver.CHOOSE_FIRST_UNBOUND,
Solver.ASSIGN_MIN_VALUE);
DecisionBuilder main_phase =
solver.Compose(long_phase, short_phase, obj_phase);
solver.NewSearch(main_phase, objective_monitor);
while (solver.NextSolution())
{
Console.WriteLine("\nLast used slot: " + (last_slot_var.Value()));
Console.WriteLine("Speakers (start..end):");
for (int s = 0; s < number_of_speakers; s++)
{
long sstart = starts[s].Value();
Console.WriteLine(" - speaker {0,2}: {1,2}..{2,2}", (s + 1),
sstart, (sstart + durations[s] - 1));
}
}
Console.WriteLine("\nSolutions: {0}", solver.Solutions());
Console.WriteLine("WallTime: {0}ms", solver.WallTime());
Console.WriteLine("Failures: {0}", solver.Failures());
Console.WriteLine("Branches: {0} ", solver.Branches());
solver.EndSearch();
}
private void Model()
{
/* Building basic task data structures */
for (int i = 0; i < tasks.Length; i++)
{
/* Create a new set of possible IntervalVars & IntVar to decide
* which one (and only 1) is performed */
taskStructures[i] = new TaskAlternative(tasks[i]);
/* Container to use when posting constraints */
location2Task[tasks[i].LocationId][tasks[i].TaskPosition] = taskStructures[i];
/* Get task type */
int taskType = tasks[i].TaskType;
/* Possible tool for this task */
List <Tool> tools = taskType2Tool[taskType];
bool optional = tools.Count > 1;
/* List of boolean variables. If performedOnTool[t] == true then
* the task is performed on tool t */
List <IntVar> performedOnTool = new List <IntVar>();
for (int t = 0; t < tools.Count; t++)
{
/* Creating an IntervalVar. If tools.Count > 1 the intervalVar
* is *OPTIONAL* */
int toolId = tools[t].Id;
Debug.Assert(tasks[i].Durations.ContainsKey(toolId));
int duration = tasks[i].Durations[toolId];
string name = "J " + tasks[i].Id + " [" + toolId + "]";
IntervalVar intervalVar;
if (taskType == factoryData.Inspection)
{
/* We set a 0 time if the task is an inspection */
duration = 0;
intervalVar = solver.MakeFixedDurationIntervalVar(0, horizon, duration, optional, name);
IntVar start = intervalVar.SafeStartExpr(-1).Var();
intervalVar.SafeStartExpr(-1).Var().SetValues(factoryData.InspectionStarts);
}
else
{
intervalVar = solver.MakeFixedDurationIntervalVar(0, horizon, duration, optional, name);
}
taskStructures[i].Intervals.Add(intervalVar);
tool2Task[toolId].Add(intervalVar);
toolIntervalVar2TaskId[toolId].Add(i);
/* Collecting all the bool vars, even if they are optional */
performedOnTool.Add(intervalVar.PerformedExpr().Var());
}
/* Linking the bool var to a single integer variable: */
/* if alternativeToolVar == t <=> performedOnTool[t] == true */
string alternativeName = "J " + tasks[i].Id;
IntVar alternativeToolVar = solver.MakeIntVar(0, tools.Count - 1, alternativeName);
taskStructures[i].ToolVar = alternativeToolVar;
solver.Add(solver.MakeMapDomain(alternativeToolVar, performedOnTool.ToArray()));
Debug.Assert(performedOnTool.ToArray().Length == alternativeToolVar.Max() + 1);
selectedTool.Add(alternativeToolVar);
}
/* Creates precedences on a work Location in order to enforce a
* fully ordered set within the same location
*/
for (int d = 0; d < location2Task.Length; d++)
{
for (int i = 0; i < location2Task[d].Length - 1; i++)
{
TaskAlternative task1 = location2Task[d][i];
TaskAlternative task2 = location2Task[d][i + 1];
/* task1 must end before task2 starts */
/* Adding precedence for each possible alternative pair */
for (int t1 = 0; t1 < task1.Intervals.Count(); t1++)
{
IntervalVar task1Alternative = task1.Intervals[t1];
for (int t2 = 0; t2 < task2.Intervals.Count(); t2++)
{
IntervalVar task2Alternative = task2.Intervals[t2];
Constraint precedence = solver.MakeIntervalVarRelation(
task2Alternative, Solver.STARTS_AFTER_END, task1Alternative);
solver.Add(precedence);
}
}
}
}
/* Adds disjunctive constraints on unary resources, and creates
* sequence variables. */
for (int t = 0; t < factoryData.NbTools; t++)
{
string name = "Tool " + t;
if (!factoryData.Tools[t].CanPerformTaskType(factoryData.Inspection))
{
DisjunctiveConstraint ct = solver.MakeDisjunctiveConstraint(tool2Task[t].ToArray(), name);
solver.Add(ct);
allToolSequences[t] = ct.SequenceVar();
}
PostTransitionTimeConstraints(t, true);
}
/* Collecting all tasks end for makespan objective function */
List <IntVar> intervalEnds = new List <IntVar>();
for (int i = 0; i < tasks.Length; i++)
{
foreach (IntervalVar var in taskStructures[i].Intervals)
{
intervalEnds.Add(var.SafeEndExpr(-1).Var());
}
}
/* Objective: minimize the makespan (maximum end times of all tasks) */
makespan = solver.MakeMax(intervalEnds.ToArray()).Var();
objective = solver.MakeMinimize(makespan, 1);
}
/**
*
*
* Organizing a day.
*
* Simple scheduling problem.
*
* Problem formulation from ECLiPSe:
* Slides on (Finite Domain) Constraint Logic Programming, page 38f
* http://eclipseclp.org/reports/eclipse.ppt
*
*
* Also see http://www.hakank.org/google_or_tools/organize_day.py
*
*/
private static void Solve()
{
Solver solver = new Solver("OrganizeDayIntervals");
int n = 4;
int work = 0;
int mail = 1;
int shop = 2;
int bank = 3;
// the valid times of the day
int begin = 9;
int end = 17;
// tasks
int[] tasks = { work, mail, shop, bank };
// durations
int[] durations = { 4, 1, 2, 1 };
// Arrays for interval variables.
int[] starts_max = { begin, begin, begin, begin };
int[] ends_max = { end - 4, end - 1, end - 2, end - 1 };
// task [i,0] must be finished before task [i,1]
int[,] before_tasks = { { bank, shop }, { mail, work } };
//
// Decision variables
//
IntervalVar[] intervals =
solver.MakeFixedDurationIntervalVarArray(n, starts_max, ends_max, durations, false, "task");
//
// Constraints
//
DisjunctiveConstraint disjunctive = intervals.Disjunctive("Sequence");
solver.Add(disjunctive);
// specific constraints
for (int t = 0; t < before_tasks.GetLength(0); t++)
{
int before = before_tasks[t, 0];
int after = before_tasks[t, 1];
solver.Add(intervals[after].StartsAfterEnd(intervals[before]));
}
solver.Add(intervals[work].StartsAfter(11));
//
// Search
//
SequenceVar var = disjunctive.SequenceVar();
SequenceVar[] seq_array = new SequenceVar[] { var };
DecisionBuilder db = solver.MakePhase(seq_array, Solver.SEQUENCE_DEFAULT);
solver.NewSearch(db);
while (solver.NextSolution())
{
foreach (int t in tasks)
{
Console.WriteLine(intervals[t].ToString());
}
Console.WriteLine();
}
Console.WriteLine("\nSolutions: {0}", solver.Solutions());
Console.WriteLine("WallTime: {0}ms", solver.WallTime());
Console.WriteLine("Failures: {0}", solver.Failures());
Console.WriteLine("Branches: {0} ", solver.Branches());
solver.EndSearch();
}
static void Main(string[] args)
{
InitTaskList();
int taskCount = GetTaskCount();
Solver solver = new Solver("ResourceConstraintScheduling");
IntervalVar[] tasks = new IntervalVar[taskCount];
IntVar[] taskChoosed = new IntVar[taskCount];
IntVar[] makeSpan = new IntVar[GetEndTaskCount()];
int endJobCounter = 0;
foreach (Job j in myJobList)
{
IntVar[] tmp = new IntVar[j.AlternativeTasks.Count];
int i = 0;
foreach (Task t in j.AlternativeTasks)
{
long ti = taskIndexes[t.Name];
taskChoosed[ti] = solver.MakeIntVar(0, 1, t.Name + "_choose");
tmp[i++] = taskChoosed[ti];
tasks[ti] = solver.MakeFixedDurationIntervalVar(
0, 100000, t.Duration, false, t.Name + "_interval");
if (j.Successor == null)
{
makeSpan[endJobCounter++] = tasks[ti].EndExpr().Var();
}
if (!tasksToEquipment.ContainsKey(t.Equipment))
{
tasksToEquipment[t.Equipment] = new List <IntervalVar>();
}
tasksToEquipment[t.Equipment].Add(tasks[ti]);
}
solver.Add(IntVarArrayHelper.Sum(tmp) == 1);
}
List <SequenceVar> all_seq = new List <SequenceVar>();
foreach (KeyValuePair <long, List <IntervalVar> > pair in tasksToEquipment)
{
DisjunctiveConstraint dc = solver.MakeDisjunctiveConstraint(
pair.Value.ToArray(), pair.Key.ToString());
solver.Add(dc);
all_seq.Add(dc.SequenceVar());
}
IntVar objective_var = solver.MakeMax(makeSpan).Var();
OptimizeVar objective_monitor = solver.MakeMinimize(objective_var, 1);
DecisionBuilder sequence_phase =
solver.MakePhase(all_seq.ToArray(), Solver.SEQUENCE_DEFAULT);
DecisionBuilder objective_phase =
solver.MakePhase(objective_var, Solver.CHOOSE_FIRST_UNBOUND,
Solver.ASSIGN_MIN_VALUE);
DecisionBuilder main_phase = solver.Compose(sequence_phase, objective_phase);
const int kLogFrequency = 1000000;
VoidToString prefix = new Prefix();
SearchMonitor search_log =
solver.MakeSearchLog(kLogFrequency, objective_monitor, prefix);
SolutionCollector collector = solver.MakeLastSolutionCollector();
collector.Add(all_seq.ToArray());
collector.AddObjective(objective_var);
if (solver.Solve(main_phase, search_log, objective_monitor, null, collector))
{
Console.Out.WriteLine("Optimal solution = " + collector.ObjectiveValue(0));
}
else
{
Console.Out.WriteLine("No solution.");
}
}
public void RunJobShopScheduling(String solverType)
{
Solver solver = new Solver(solverType);
if (solver == null)
{
Console.WriteLine("JobShop failed to create a solver " + solverType);
return;
}
// All tasks
Dictionary <string, IntervalVar> allTasks = new Dictionary <string, IntervalVar>();
// Creates jobs
for (int i = 0; i < allJobs.Count; i++)
{
for (int j = 0; j < machines.ElementAt(i).Count; j++)
{
IntervalVar oneTask = solver.MakeFixedDurationIntervalVar(0,
horizon,
processingTimes.ElementAt(i).ElementAt(j),
false,
"Job_" + i + "_" + j);
//Console.WriteLine("Job_" + i + "_" + j);
allTasks.Add("Job_" + i + "_" + j, oneTask);
}
}
// Create sequence variables and add disjuctive constraints
List <SequenceVar> allSequences = new List <SequenceVar>();
foreach (var machine in allMachines)
{
List <IntervalVar> machinesJobs = new List <IntervalVar>();
for (int i = 0; i < allJobs.Count; i++)
{
for (int k = 0; k < machines.ElementAt(i).Count; k++)
{
if (machines.ElementAt(i).ElementAt(k) == machine)
{
machinesJobs.Add(allTasks["Job_" + i + "_" + k]);
}
}
}
DisjunctiveConstraint disj = solver.MakeDisjunctiveConstraint(machinesJobs.ToArray(),
"machine " + machine);
allSequences.Add(disj.SequenceVar());
solver.Add(disj);
}
// Add conjunctive constraints
foreach (var job in allJobs)
{
for (int j = 0; j < machines.ElementAt(job).Count - 1; j++)
{
solver.Add(allTasks["Job_" + job + "_" + (j + 1)].StartsAfterEnd(allTasks["Job_" + job + "_" + j]));
}
}
// Set the objective
IntVar[] allEnds = new IntVar[jobsCount];
for (int i = 0; i < allJobs.Count; i++)
{
allEnds[i] = allTasks["Job_" + i + "_" + (machines.ElementAt(i).Count - 1)].EndExpr().Var();
}
// Objective: minimize the makespan (maximum end times of all tasks)
// of the problem.
IntVar objectiveVar = solver.MakeMax(allEnds).Var();
OptimizeVar objectiveMonitor = solver.MakeMinimize(objectiveVar, 1);
// Create search phases
DecisionBuilder sequencePhase = solver.MakePhase(allSequences.ToArray(), Solver.SEQUENCE_DEFAULT);
DecisionBuilder varsPhase = solver.MakePhase(objectiveVar, Solver.CHOOSE_FIRST_UNBOUND, Solver.ASSIGN_MIN_VALUE);
// The main decision builder (ranks all tasks, then fixes the
// objectiveVariable).
DecisionBuilder mainPhase = solver.Compose(sequencePhase, varsPhase);
SolutionCollector collector = solver.MakeLastSolutionCollector();
collector.Add(allSequences.ToArray());
collector.Add(objectiveVar);
foreach (var i in allMachines)
{
SequenceVar sequence = allSequences.ElementAt(i);
long sequenceCount = sequence.Size();
for (int j = 0; j < sequenceCount; j++)
{
IntervalVar t = sequence.Interval(j);
collector.Add(t.StartExpr().Var());
collector.Add(t.EndExpr().Var());
}
}
// Search.
bool solutionFound = solver.Solve(mainPhase, null, objectiveMonitor, null, collector);
if (solutionFound)
{
//The index of the solution from the collector
const int SOLUTION_INDEX = 0;
Assignment solution = collector.Solution(SOLUTION_INDEX);
string solLine = "";
string solLineTasks = "";
Console.WriteLine("Time Intervals for Tasks\n");
List <List <TimeSpan> > tuplesSolution = new List <List <TimeSpan> >();
for (int m = 0; m < this.machinesCount; m++)
{
//Console.WriteLine("MachineCount: " + this.machinesCount);
solLine = "Machine " + m + " :";
solLineTasks = "Machine " + m + ": ";
SequenceVar seq = allSequences.ElementAt(m);
int[] storedSequence = collector.ForwardSequence(SOLUTION_INDEX, seq);
foreach (int taskIndex in storedSequence)
{
//Console.WriteLine("taskIndex: " + taskIndex);
IntervalVar task = seq.Interval(taskIndex);
solLineTasks += task.Name() + " ";
//Console.WriteLine("Len: " + storedSequence.Length);
}
// First GreenTime
//TimeSpan timeToAdd = tuplesSolution.First().Last();
TimeSpan timeEndBucket = this.bucketInfo.EndBucket;
TimeSpan timeStartBucket = this.bucketInfo.StartBucket;
int solutionSize = tuplesSolution.Count;
bool isEnd = false;
List <int> list_id = jobIds.ElementAt(m);
// Adding GreenTime to Solution
while (timeStartBucket.CompareTo(timeEndBucket) < 0)
{
foreach (int taskIndex in storedSequence)
{
IntervalVar task = seq.Interval(taskIndex);
var startValue = TimeSpan.FromSeconds(collector.Value(0, task.StartExpr().Var()));
var endValue = TimeSpan.FromSeconds(collector.Value(0, task.EndExpr().Var()));
TimeSpan greenTime = endValue.Subtract(startValue);
TimeSpan timeEnd;
timeEnd = timeStartBucket.Add(greenTime);
List <TimeSpan> tuple = new List <TimeSpan>();
tuple.Add(timeStartBucket);
if (timeEndBucket.CompareTo(timeEnd) < 0)
{
timeEnd = timeEndBucket;
isEnd = true;
}
tuple.Add(timeEnd);
tuplesSolution.Add(tuple);
if (taskIndex + 1 < list_id.Count() && list_id.ElementAt(taskIndex) == list_id.ElementAt(taskIndex + 1))
{
timeStartBucket = timeStartBucket.Add(TimeSpan.FromSeconds(this.cycleTime));
}
else
{
timeStartBucket = timeEnd;
}
if (isEnd)
{
break;
}
}
}
//
// Saving the Solution to a XML file
//
JobShop.save(m, tuplesSolution);
//solLine += "\n";
//solLineTasks += "\n";
//Console.WriteLine(solLineTasks);
//Console.WriteLine(solLine);
}
}
else
{
Console.WriteLine("No solution found!");
}
}
public void RunJobShopScheduling(String solverType)
{
Solver solver = new Solver(solverType);
if (solver == null)
{
Console.WriteLine("JobShop failed to create a solver " + solverType);
return;
}
// All tasks
Dictionary <string, IntervalVar> allTasks = new Dictionary <string, IntervalVar>();
// Creates jobs
for (int i = 0; i < allJobs.Count; i++)
{
for (int j = 0; j < machines.ElementAt(i).Count; j++)
{
IntervalVar oneTask = solver.MakeFixedDurationIntervalVar(0,
horizon,
processingTimes.ElementAt(i).ElementAt(j),
false,
"Job_" + i + "_" + j);
allTasks.Add("Job_" + i + "_" + j, oneTask);
}
}
// Create sequence variables and add disjuctive constraints
List <SequenceVar> allSequences = new List <SequenceVar>();
foreach (var machine in allMachines)
{
List <IntervalVar> machinesJobs = new List <IntervalVar>();
for (int i = 0; i < allJobs.Count; i++)
{
for (int k = 0; k < machines.ElementAt(i).Count; k++)
{
if (machines.ElementAt(i).ElementAt(k) == machine)
{
machinesJobs.Add(allTasks["Job_" + i + "_" + k]);
}
}
}
DisjunctiveConstraint disj = solver.MakeDisjunctiveConstraint(machinesJobs.ToArray(),
"machine " + machine);
allSequences.Add(disj.SequenceVar());
solver.Add(disj);
}
// Add conjunctive constraints
foreach (var job in allJobs)
{
for (int j = 0; j < machines.ElementAt(job).Count - 1; j++)
{
solver.Add(allTasks["Job_" + job + "_" + (j + 1)].StartsAfterEnd(allTasks["Job_" + job + "_" + j]));
}
}
// Set the objective
IntVar[] allEnds = new IntVar[jobsCount];
for (int i = 0; i < allJobs.Count; i++)
{
allEnds[i] = allTasks["Job_" + i + "_" + (machines.ElementAt(i).Count - 1)].EndExpr().Var();
}
// Objective: minimize the makespan (maximum end times of all tasks)
// of the problem.
IntVar objectiveVar = solver.MakeMax(allEnds).Var();
OptimizeVar objectiveMonitor = solver.MakeMinimize(objectiveVar, 1);
// Create search phases
DecisionBuilder sequencePhase = solver.MakePhase(allSequences.ToArray(), Solver.SEQUENCE_DEFAULT);
DecisionBuilder varsPhase = solver.MakePhase(objectiveVar, Solver.CHOOSE_FIRST_UNBOUND, Solver.ASSIGN_MIN_VALUE);
// The main decision builder (ranks all tasks, then fixes the
// objectiveVariable).
DecisionBuilder mainPhase = solver.Compose(sequencePhase, varsPhase);
SolutionCollector collector = solver.MakeLastSolutionCollector();
collector.Add(allSequences.ToArray());
collector.Add(objectiveVar);
foreach (var i in allMachines)
{
SequenceVar sequence = allSequences.ElementAt(i);
long sequenceCount = sequence.Size();
for (int j = 0; j < sequenceCount; j++)
{
IntervalVar t = sequence.Interval(j);
collector.Add(t.StartExpr().Var());
collector.Add(t.EndExpr().Var());
}
}
// Search.
bool solutionFound = solver.Solve(mainPhase, null, objectiveMonitor, null, collector);
if (solutionFound)
{
//The index of the solution from the collector
const int SOLUTION_INDEX = 0;
Assignment solution = collector.Solution(SOLUTION_INDEX);
string solLine = "";
string solLineTasks = "";
Console.WriteLine("Time Intervals for Tasks\n");
for (int m = 0; m < this.machinesCount; m++)
{
//Console.WriteLine("MachineCount: " + this.machinesCount);
solLine = "Machine " + m + " :";
solLineTasks = "Machine " + m + ": ";
SequenceVar seq = allSequences.ElementAt(m);
int[] storedSequence = collector.ForwardSequence(SOLUTION_INDEX, seq);
foreach (int taskIndex in storedSequence)
{
//Console.WriteLine("taskIndex: " + taskIndex);
IntervalVar task = seq.Interval(taskIndex);
solLineTasks += task.Name() + " ";
//Console.WriteLine("Len: " + storedSequence.Length);
}
foreach (int taskIndex in storedSequence)
{
IntervalVar task = seq.Interval(taskIndex);
string solTemp = "[" + collector.Value(0, task.StartExpr().Var()) + ",";
solTemp += collector.Value(0, task.EndExpr().Var()) + "] ";
solLine += solTemp;
}
//solLine += "\n";
solLineTasks += "\n";
//Console.WriteLine(solLineTasks);
Console.WriteLine(solLine);
}
}
else
{
Console.WriteLine("No solution found!");
}
}
public static void Solve(FlexibleJobShopData data, bool chatty = false)
{
// Compute horizon
var horizon = data.JobList.Sum(
j => j.TaskList.Sum(
t => t.Durations.Max()));
// ----- Create all intervals and vars -----
/*
* // Use some profiling and change the default parameters of the solver
* SolverParameters solverParams = new SolverParameters();
* // Change the profile level
* solverParams.profile_level = SolverParameters.NORMAL_PROFILING;
* // Constraint programming engine
* Solver solver = new Solver("JobShop", solverParams);
*/
// Constraint programming engine
Solver solver = new Solver($"FlexibleJobShop: {data.Name}");
// Initialize dictionaries to hold references to task intervals
var tasksByJobId = new Dictionary <uint, List <TaskAlternative> >();
foreach (var job in data.JobList)
{
tasksByJobId[job.Id] = new List <TaskAlternative>(job.TaskList.Count);
}
var tasksByMachineId = new Dictionary <uint, IntervalVarVector>();
foreach (var machine in data.MachineList)
{
tasksByMachineId[machine.Id] = new IntervalVarVector();
}
// Creates all individual interval variables and collect in dictionaries
foreach (var job in data.JobList)
{
foreach (var task in job.TaskList)
{
var alternative = new TaskAlternative(job.Id);
tasksByJobId[job.Id].Add(alternative);
var activeVariables = new IntVarVector();
var hasAlternatives = task.AlternativesCount > 1;
for (int alt = 0; alt < task.AlternativesCount; alt++)
{
var machine = task.Machines[alt];
var duration = task.Durations[alt];
var name = $"{task.Name}; Alternative {alt}: {machine.Name}, Duration {duration}";
IntervalVar interval = solver.MakeFixedDurationIntervalVar(0, horizon, duration, hasAlternatives, name);
alternative.Add(interval);
tasksByMachineId[machine.Id].Add(interval);
if (hasAlternatives)
{
activeVariables.Add(interval.PerformedExpr().Var());
}
}
alternative.AlternativeVar = solver.MakeIntVar(0, task.AlternativesCount - 1, task.Name);
if (hasAlternatives)
{
solver.Add(solver.MakeMapDomain(alternative.AlternativeVar, activeVariables));
}
}
}
// ----- Create model -----
// Create precedences inside jobs
foreach (var taskAltList in tasksByJobId.Values)
{
for (int i = 0; i < taskAltList.Count - 1; i++)
{
TaskAlternative currentTaskAlt = taskAltList[i];
TaskAlternative nextTaskAlt = taskAltList[i + 1];
foreach (var alt1 in currentTaskAlt)
{
foreach (var alt2 in nextTaskAlt)
{
solver.Add(solver.MakeIntervalVarRelation(
alt2, Solver.STARTS_AFTER_END, alt1));
}
}
}
}
// Collect alternative variables.
IntVarVector alternativeVariableVec = new IntVarVector();
foreach (var taskAltList in tasksByJobId.Values)
{
foreach (var taskAlt in taskAltList)
{
if (!taskAlt.AlternativeVar.Bound())
{
alternativeVariableVec.Add(taskAlt.AlternativeVar);
}
}
}
// Add disjunctive constraints on unary resources, and create
// sequence variables. A sequence variable is a dedicated variable
// whose job is to sequence interval variables.
SequenceVarVector allSequences = new SequenceVarVector();
foreach (var machine in data.MachineList)
{
DisjunctiveConstraint disjCt = solver.MakeDisjunctiveConstraint(
tasksByMachineId[machine.Id], machine.Name);
solver.Add(disjCt);
allSequences.Add(disjCt.SequenceVar());
}
// Create array of end_times of jobs
IntVarVector endsVec = new IntVarVector();
foreach (var taskAltList in tasksByJobId.Values)
{
TaskAlternative lastTaskAlt = taskAltList.Last();
foreach (var alt in lastTaskAlt)
{
endsVec.Add(alt.SafeEndExpr(-1).Var());
}
}
// Objective: minimize the makespan (maximum end times of all tasks)
// of the problem.
IntVar objectiveVar = solver.MakeMax(endsVec).Var();
OptimizeVar objectiveMonitor = solver.MakeMinimize(objectiveVar, 1);
// ----- Search monitors and decision builder -----
// This decision builder will assign all alternative variables.
DecisionBuilder alternativePhase = solver.MakePhase(alternativeVariableVec, Solver.CHOOSE_MIN_SIZE, Solver.ASSIGN_MIN_VALUE);
// This decision builder will rank all tasks on all machines.
DecisionBuilder sequencePhase = solver.MakePhase(allSequences, Solver.SEQUENCE_DEFAULT);
// After the ranking of tasks, the schedule is still loose and any
// task can be postponed at will. But, because the problem is now a PERT
// (http://en.wikipedia.org/wiki/Program_Evaluation_and_Review_Technique),
// we can schedule each task at its earliest start time. This is
// conveniently done by fixing the objective variable to its
// minimum value.
DecisionBuilder objectivePhase = solver.MakePhase(objectiveVar, Solver.CHOOSE_FIRST_UNBOUND, Solver.ASSIGN_MIN_VALUE);
// The main decision builder (ranks all tasks, then fixes the
// objective_variable).
DecisionBuilder mainPhase = solver.Compose(alternativePhase, sequencePhase, objectivePhase);
// Search log
const int kLogFrequency = 1000000;
SearchMonitor searchLog = solver.MakeSearchLog(kLogFrequency, objectiveMonitor);
const long FLAGS_time_limit_in_ms = 1000 * 60 * 20;
SearchLimit limit = null;
if (FLAGS_time_limit_in_ms > 0)
{
limit = solver.MakeTimeLimit(FLAGS_time_limit_in_ms);
}
SolutionCollector collector = solver.MakeLastSolutionCollector();
collector.AddObjective(objectiveVar);
collector.Add(alternativeVariableVec);
collector.Add(allSequences);
foreach (var taskVec in tasksByMachineId.Values)
{
foreach (var task in taskVec)
{
collector.Add(task.StartExpr().Var());
}
}
// ----- Search -----
bool solutionFound = solver.Solve(mainPhase, searchLog, objectiveMonitor, limit, collector);
if (solutionFound)
{
// The index of the solution from the collector
const int SOLUTION_INDEX = 0;
Assignment solution = collector.Solution(SOLUTION_INDEX);
Console.WriteLine();
uint machineIdx = 0;
foreach (var seq in allSequences)
{
machineIdx++;
var taskSeq = collector.ForwardSequence(SOLUTION_INDEX, seq);
Console.WriteLine($"{seq.Name()}:");
Console.WriteLine(" Tasks: " + string.Join(", ", taskSeq));
//foreach (var taskIndex in storedSequence)
//{
// IntervalVar task = sequence.Interval(taskIndex);
// long startMin = solution.StartMin(task);
// long startMax = solution.StartMax(task);
// if (startMin == startMax)
// {
// Console.WriteLine($"Task {task.Name()} starts at {startMin}.");
// }
// else
// {
// Console.WriteLine($"Task {task.Name()} starts between {startMin} and {startMax}.");
// }
//}
Console.WriteLine();
Console.Write(" Starting times:");
foreach (var s in taskSeq)
{
Console.Write(" " + collector.Value(0, tasksByMachineId[machineIdx][s].StartExpr().Var()).ToString());
}
Console.WriteLine();
}
//var x = tasksByMachineId[1][0].StartExpr().Var();
//var xValStr = collector.Value(0, x).ToString();
Console.WriteLine("objective function value = " + solution.ObjectiveValue()); //TEMP
}
// Save profile in file
//solver.ExportProfilingOverview("profile.txt");
// Done
solver.EndSearch();
}
public static void Main(String[] args)
{
InitTaskList();
Solver solver = new Solver("Jobshop");
// ----- Creates all Intervals and vars -----
// All tasks
List <IntervalVar> allTasks = new List <IntervalVar>();
// Stores all tasks attached interval variables per job.
List <List <IntervalVar> >
jobsToTasks = new List <List <IntervalVar> >(jobsCount);
// machinesToTasks stores the same interval variables as above, but
// grouped my machines instead of grouped by jobs.
List <List <IntervalVar> >
machinesToTasks = new List <List <IntervalVar> >(machinesCount);
for (int i = 0; i < machinesCount; i++)
{
machinesToTasks.Add(new List <IntervalVar>());
}
// Creates all individual interval variables.
foreach (List <Task> job in myJobList)
{
jobsToTasks.Add(new List <IntervalVar>());
foreach (Task task in job)
{
IntervalVar oneTask = solver.MakeFixedDurationIntervalVar(
0, horizon, task.Duration, false, task.Name);
jobsToTasks[task.JobId].Add(oneTask);
allTasks.Add(oneTask);
machinesToTasks[task.Machine].Add(oneTask);
}
}
// ----- Creates model -----
// Creates precedences inside jobs.
foreach (List <IntervalVar> jobToTask in jobsToTasks)
{
int tasksCount = jobToTask.Count;
for (int task_index = 0; task_index < tasksCount - 1; ++task_index)
{
IntervalVar t1 = jobToTask[task_index];
IntervalVar t2 = jobToTask[task_index + 1];
Constraint prec =
solver.MakeIntervalVarRelation(t2, Solver.STARTS_AFTER_END, t1);
solver.Add(prec);
}
}
// Adds disjunctive constraints on unary resources, and creates
// sequence variables. A sequence variable is a dedicated variable
// whose job is to sequence interval variables.
SequenceVar[] allSequences = new SequenceVar[machinesCount];
for (int machineId = 0; machineId < machinesCount; ++machineId)
{
string name = "Machine_" + machineId;
DisjunctiveConstraint ct =
solver.MakeDisjunctiveConstraint(machinesToTasks[machineId].ToArray(),
name);
solver.Add(ct);
allSequences[machineId] = ct.SequenceVar();
}
// Creates array of end_times of jobs.
IntVar[] allEnds = new IntVar[jobsCount];
for (int i = 0; i < jobsCount; i++)
{
IntervalVar task = jobsToTasks[i].Last();
allEnds[i] = task.EndExpr().Var();
}
// Objective: minimize the makespan (maximum end times of all tasks)
// of the problem.
IntVar objectiveVar = solver.MakeMax(allEnds).Var();
OptimizeVar objectiveMonitor = solver.MakeMinimize(objectiveVar, 1);
// ----- Search monitors and decision builder -----
// This decision builder will rank all tasks on all machines.
DecisionBuilder sequencePhase =
solver.MakePhase(allSequences, Solver.SEQUENCE_DEFAULT);
// After the ranking of tasks, the schedule is still loose and any
// task can be postponed at will. But, because the problem is now a PERT
// (http://en.wikipedia.org/wiki/Program_Evaluation_and_Review_Technique),
// we can schedule each task at its earliest start time. This iscs
// conveniently done by fixing the objective variable to its
// minimum value.
DecisionBuilder objPhase = solver.MakePhase(
objectiveVar, Solver.CHOOSE_FIRST_UNBOUND, Solver.ASSIGN_MIN_VALUE);
// The main decision builder (ranks all tasks, then fixes the
// objectiveVariable).
DecisionBuilder mainPhase = solver.Compose(sequencePhase, objPhase);
// Search log.
const int kLogFrequency = 1000000;
SearchMonitor searchLog =
solver.MakeSearchLog(kLogFrequency, objectiveMonitor);
SearchLimit limit = null;
if (timeLimitInMs > 0)
{
limit = solver.MakeTimeLimit(timeLimitInMs);
}
SolutionCollector collector = solver.MakeLastSolutionCollector();
collector.Add(allSequences);
collector.Add(allTasks.ToArray());
// Search.
bool solutionFound = solver.Solve(mainPhase, searchLog, objectiveMonitor,
limit, collector);
if (solutionFound)
{
//The index of the solution from the collector
const int SOLUTION_INDEX = 0;
Assignment solution = collector.Solution(SOLUTION_INDEX);
for (int m = 0; m < machinesCount; ++m)
{
Console.WriteLine("Machine " + m + " :");
SequenceVar seq = allSequences[m];
int[] storedSequence = collector.ForwardSequence(SOLUTION_INDEX, seq);
foreach (int taskIndex in storedSequence)
{
IntervalVar task = seq.Interval(taskIndex);
long startMin = solution.StartMin(task);
long startMax = solution.StartMax(task);
if (startMin == startMax)
{
Console.WriteLine("Task " + task.Name() + " starts at " +
startMin + ".");
}
else
{
Console.WriteLine("Task " + task.Name() + " starts between " +
startMin + " and " + startMax + ".");
}
}
}
}
else
{
Console.WriteLine("No solution found!");
}
}
