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ortools-clone/examples/csharp/slow_scheduling.cs
2014-01-15 23:48:03 +00:00

285 lines
11 KiB
C#

//
// Copyright 2013 Google
//
// 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 Google.OrTools.ConstraintSolver;
using Google.OrTools.Graph;
using System.Collections.Generic;
using System.Diagnostics;
using System.Linq;
using System;
public class SpeakerScheduling
{
public class FlowAssign : NetDecisionBuilder
{
public FlowAssign(IntVar[] vars, int first_slot, IntVar last_slot_var)
{
vars_ = vars;
first_slot_ = first_slot;
last_slot_var_ = last_slot_var;
}
public override Decision Next(Solver solver)
{
int large = 100000;
int number_of_variables = vars_.Length;
long last_slot = last_slot_var_.Max();
// Lets build a bipartite graph with equal number of nodes left and right.
// Variables will be on the left, slots on the right.
// We will add dummy variables when needed.
// Arcs will have a cost x is slot x is possible for a variable, a large
// number otherwise. For dummy variables, the cost will be 0 always.
LinearSumAssignment matching = new LinearSumAssignment();
for (int speaker = 0; speaker < number_of_variables; ++speaker)
{
IntVar var = vars_[speaker];
for (int value = first_slot_; value <= last_slot; ++value)
{
if (var.Contains(value))
{
matching.AddArcWithCost(speaker, value - first_slot_, value);
}
else
{
matching.AddArcWithCost(speaker, value - first_slot_, large);
}
}
}
// The Matching algorithms expect the same number of left and right nodes.
// So we fill the rest with dense zero-cost arcs.
for (int dummy = number_of_variables;
dummy <= last_slot - first_slot_; ++dummy) {
for (int value = first_slot_; value <= last_slot; ++value)
{
matching.AddArcWithCost(dummy, value - first_slot_, 0);
}
}
if (matching.Solve() == LinearSumAssignment.OPTIMAL &&
matching.OptimalCost() < large) // No violated arcs.
{
for (int speaker = 0; speaker < number_of_variables; ++speaker)
{
vars_[speaker].SetValue(matching.RightMate(speaker) + first_slot_);
}
} else {
solver.Fail();
}
return null;
}
private IntVar[] vars_;
private int first_slot_;
private IntVar last_slot_var_;
}
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();
}
public static void Main(String[] args)
{
int start = 1;
if (args.Length == 1)
{
start = int.Parse(args[0]);
}
Stopwatch s = new Stopwatch();
s.Start();
for (int i = start; i < 40; i++)
{
Solve(i);
}
s.Stop();
Console.WriteLine("Finished in " + s.ElapsedMilliseconds + " ms");
}
}