[CP-SAT] Add AtMostOne/AtLeastOne/ExactlyOne constraint in all languages; rewrite linear expressions in java

ortools/sat/samples/ChannelingSampleSat.java

@@ -30,24 +30,23 @@ public class ChannelingSampleSat {
     CpModel model = new CpModel();
 
     // Declare our two primary variables.
-    IntVar x = model.newIntVar(0, 10, "x");
-    IntVar y = model.newIntVar(0, 10, "y");
+    IntVar[] vars = new IntVar[] {model.newIntVar(0, 10, "x"), model.newIntVar(0, 10, "y")};
 
     // Declare our intermediate boolean variable.
     IntVar b = model.newBoolVar("b");
 
     // Implement b == (x >= 5).
-    model.addGreaterOrEqual(x, 5).onlyEnforceIf(b);
-    model.addLessOrEqual(x, 4).onlyEnforceIf(b.not());
+    model.addGreaterOrEqual(vars[0], 5).onlyEnforceIf(b);
+    model.addLessOrEqual(vars[0], 4).onlyEnforceIf(b.not());
 
     // Create our two half-reified constraints.
     // First, b implies (y == 10 - x).
-    model.addEquality(LinearExpr.sum(new IntVar[] {x, y}), 10).onlyEnforceIf(b);
+    model.addEquality(LinearExpr.sum(vars), 10).onlyEnforceIf(b);
     // Second, not(b) implies y == 0.
-    model.addEquality(y, 0).onlyEnforceIf(b.not());
+    model.addEquality(vars[1], 0).onlyEnforceIf(b.not());
 
     // Search for x values in increasing order.
-    model.addDecisionStrategy(new IntVar[] {x},
+    model.addDecisionStrategy(new IntVar[] {vars[0]},
         DecisionStrategyProto.VariableSelectionStrategy.CHOOSE_FIRST,
         DecisionStrategyProto.DomainReductionStrategy.SELECT_MIN_VALUE);
 
@@ -75,6 +74,6 @@ public class ChannelingSampleSat {
       }
 
       private IntVar[] variableArray;
-    }.init(new IntVar[] {x, y, b}));
+    }.init(new IntVar[] {vars[0], vars[1], b}));
   }
 }