forked from google/or-tools
-
Notifications
You must be signed in to change notification settings - Fork 0
/
ReifiedSampleSat.java
51 lines (44 loc) · 1.86 KB
/
ReifiedSampleSat.java
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
// 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.
package com.google.ortools.sat.samples;
import com.google.ortools.Loader;
import com.google.ortools.sat.CpModel;
import com.google.ortools.sat.IntVar;
import com.google.ortools.sat.Literal;
/**
* Reification is the action of associating a Boolean variable to a constraint. This boolean
* enforces or prohibits the constraint according to the value the Boolean variable is fixed to.
*
* <p>Half-reification is defined as a simple implication: If the Boolean variable is true, then the
* constraint holds, instead of an complete equivalence.
*
* <p>The SAT solver offers half-reification. To implement full reification, two half-reified
* constraints must be used.
*/
public class ReifiedSampleSat {
public static void main(String[] args) throws Exception {
Loader.loadNativeLibraries();
CpModel model = new CpModel();
IntVar x = model.newBoolVar("x");
IntVar y = model.newBoolVar("y");
IntVar b = model.newBoolVar("b");
// Version 1: a half-reified boolean and.
model.addBoolAnd(new Literal[] {x, y.not()}).onlyEnforceIf(b);
// Version 2: implications.
model.addImplication(b, x);
model.addImplication(b, y.not());
// Version 3: boolean or.
model.addBoolOr(new Literal[] {b.not(), x});
model.addBoolOr(new Literal[] {b.not(), y.not()});
}
}