forked from google/or-tools
-
Notifications
You must be signed in to change notification settings - Fork 0
/
techtalk_scheduling.cs
281 lines (262 loc) · 12.8 KB
/
techtalk_scheduling.cs
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
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
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
// Copyright 2010-2021 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 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.Status.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 < duration; ++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 = 17;
if (args.Length == 1)
{
start = int.Parse(args[0]);
}
Stopwatch s = new Stopwatch();
s.Start();
Solve(start);
s.Stop();
Console.WriteLine("Finished in " + s.ElapsedMilliseconds + " ms");
}
}