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RankingSampleSat.cs
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RankingSampleSat.cs
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// Copyright 2010-2024 Google LLC
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
using System;
using System.Collections.Generic;
using Google.OrTools.Sat;
public class RankingSampleSat
{
static void RankTasks(CpModel model, IntVar[] starts, ILiteral[] presences, IntVar[] ranks)
{
int num_tasks = starts.Length;
// Creates precedence variables between pairs of intervals.
ILiteral[,] precedences = new ILiteral[num_tasks, num_tasks];
for (int i = 0; i < num_tasks; ++i)
{
for (int j = 0; j < num_tasks; ++j)
{
if (i == j)
{
precedences[i, i] = presences[i];
}
else
{
BoolVar prec = model.NewBoolVar(String.Format("{0} before {1}", i, j));
precedences[i, j] = prec;
model.Add(starts[i] < starts[j]).OnlyEnforceIf(prec);
}
}
}
// Treats optional intervals.
for (int i = 0; i < num_tasks - 1; ++i)
{
for (int j = i + 1; j < num_tasks; ++j)
{
List<ILiteral> tmp_array = new List<ILiteral>();
tmp_array.Add(precedences[i, j]);
tmp_array.Add(precedences[j, i]);
tmp_array.Add(presences[i].Not());
// Makes sure that if i is not performed, all precedences are false.
model.AddImplication(presences[i].Not(), precedences[i, j].Not());
model.AddImplication(presences[i].Not(), precedences[j, i].Not());
tmp_array.Add(presences[j].Not());
// Makes sure that if j is not performed, all precedences are false.
model.AddImplication(presences[j].Not(), precedences[i, j].Not());
model.AddImplication(presences[j].Not(), precedences[j, i].Not());
// The following bool_or will enforce that for any two intervals:
// i precedes j or j precedes i or at least one interval is not
// performed.
model.AddBoolOr(tmp_array);
// Redundant constraint: it propagates early that at most one precedence
// is true.
model.AddImplication(precedences[i, j], precedences[j, i].Not());
model.AddImplication(precedences[j, i], precedences[i, j].Not());
}
}
// Links precedences and ranks.
for (int i = 0; i < num_tasks; ++i)
{
List<IntVar> tasks = new List<IntVar>();
for (int j = 0; j < num_tasks; ++j)
{
tasks.Add((IntVar)precedences[j, i]);
}
model.Add(ranks[i] == LinearExpr.Sum(tasks) - 1);
}
}
static void Main()
{
CpModel model = new CpModel();
// Three weeks.
int horizon = 100;
int num_tasks = 4;
IntVar[] starts = new IntVar[num_tasks];
IntVar[] ends = new IntVar[num_tasks];
IntervalVar[] intervals = new IntervalVar[num_tasks];
ILiteral[] presences = new ILiteral[num_tasks];
IntVar[] ranks = new IntVar[num_tasks];
ILiteral true_var = model.TrueLiteral();
// Creates intervals, half of them are optional.
for (int t = 0; t < num_tasks; ++t)
{
starts[t] = model.NewIntVar(0, horizon, String.Format("start_{0}", t));
int duration = t + 1;
ends[t] = model.NewIntVar(0, horizon, String.Format("end_{0}", t));
if (t < num_tasks / 2)
{
intervals[t] = model.NewIntervalVar(starts[t], duration, ends[t], String.Format("interval_{0}", t));
presences[t] = true_var;
}
else
{
presences[t] = model.NewBoolVar(String.Format("presence_{0}", t));
intervals[t] = model.NewOptionalIntervalVar(starts[t], duration, ends[t], presences[t],
String.Format("o_interval_{0}", t));
}
// Ranks = -1 if and only if the tasks is not performed.
ranks[t] = model.NewIntVar(-1, num_tasks - 1, String.Format("rank_{0}", t));
}
// Adds NoOverlap constraint.
model.AddNoOverlap(intervals);
// Adds ranking constraint.
RankTasks(model, starts, presences, ranks);
// Adds a constraint on ranks.
model.Add(ranks[0] < ranks[1]);
// Creates makespan variable.
IntVar makespan = model.NewIntVar(0, horizon, "makespan");
for (int t = 0; t < num_tasks; ++t)
{
model.Add(ends[t] <= makespan).OnlyEnforceIf(presences[t]);
}
// Minimizes makespan - fixed gain per tasks performed.
// As the fixed cost is less that the duration of the last interval,
// the solver will not perform the last interval.
IntVar[] presences_as_int_vars = new IntVar[num_tasks];
for (int t = 0; t < num_tasks; ++t)
{
presences_as_int_vars[t] = (IntVar)presences[t];
}
model.Minimize(2 * makespan - 7 * LinearExpr.Sum(presences_as_int_vars));
// Creates a solver and solves the model.
CpSolver solver = new CpSolver();
CpSolverStatus status = solver.Solve(model);
if (status == CpSolverStatus.Optimal)
{
Console.WriteLine(String.Format("Optimal cost: {0}", solver.ObjectiveValue));
Console.WriteLine(String.Format("Makespan: {0}", solver.Value(makespan)));
for (int t = 0; t < num_tasks; ++t)
{
if (solver.BooleanValue(presences[t]))
{
Console.WriteLine(String.Format("Task {0} starts at {1} with rank {2}", t, solver.Value(starts[t]),
solver.Value(ranks[t])));
}
else
{
Console.WriteLine(
String.Format("Task {0} in not performed and ranked at {1}", t, solver.Value(ranks[t])));
}
}
}
else
{
Console.WriteLine(String.Format("Solver exited with nonoptimal status: {0}", status));
}
}
}