mimic C++ linear API in java for CP-SAT

ortools/com/google/ortools/sat/CpModel.java

@@ -129,29 +129,15 @@ public class CpModel {
 
   // Linear constraints.
 
-  /** Add {@code lb <= sum(vars) <= ub}. */
-  public Constraint addSumConstraint(IntVar[] vars, long lb, long ub) {
-    Constraint ct = new Constraint(modelBuilder);
-    LinearConstraintProto.Builder lin = ct.getBuilder().getLinearBuilder();
-    for (IntVar var : vars) {
-      lin.addVars(var.getIndex());
-      lin.addCoeffs(1);
-    }
-    lin.addDomain(lb);
-    lin.addDomain(ub);
-    return ct;
-  }
-
   /**
-   * Add {@code sum(vars) in domain}, where domain is a flattened list of intervals similar to the
-   * one for enumerated integer variables.
+   * Adds {@code expr in domain}.
    */
-  public Constraint addSumInDomain(IntVar[] vars, Domain domain) {
+  public Constraint addLinearExpressionInDomain(LinearExpr expr, Domain domain) {
     Constraint ct = new Constraint(modelBuilder);
     LinearConstraintProto.Builder lin = ct.getBuilder().getLinearBuilder();
-    for (IntVar var : vars) {
-      lin.addVars(var.getIndex());
-      lin.addCoeffs(1);
+    for (int i = 0; i < expr.numElements(); ++i) {
+      lin.addVars(expr.getVariable(i).getIndex());
+      lin.addCoeffs(expr.getCoefficient(i));
     }
     for (long b : domain.flattenedIntervals()) {
       lin.addDomain(b);
@@ -159,201 +145,75 @@ public class CpModel {
     return ct;
   }
 
-  /** Add {@code sum(vars) == value}. */
-  public Constraint addSumEqual(IntVar[] vars, long value) {
-    return addSumConstraint(vars, value, value);
+  /** Adds {@code lb <= expr <= ub}. */
+  public Constraint addLinearConstraint(LinearExpr expr, long lb, long ub) {
+    return addLinearExpressionInDomain(expr, new Domain(lb, ub));
   }
 
-  /** Add {@code sum(vars) == target}. */
-  public Constraint addSumEqual(IntVar[] vars, IntVar target) {
-    int size = vars.length;
-    IntVar[] newVars = new IntVar[size + 1];
-    long[] coeffs = new long[size + 1];
-    for (int i = 0; i < size; ++i) {
-      newVars[i] = vars[i];
-      coeffs[i] = 1;
-    }
-    newVars[size] = target;
-    coeffs[size] = -1;
-    return addLinearConstraint(newVars, coeffs, 0, 0);
+  /** Adds {@code expr == value}. */
+  public Constraint addEquality(LinearExpr expr, long value) {
+    return addLinearExpressionInDomain(expr, new Domain(value));
   }
 
-  /** Add {@code lb <= sum(vars[i] * coeffs[i]) <= ub}. */
-  public Constraint addLinearConstraint(IntVar[] vars, long[] coeffs, long lb, long ub) {
-    Constraint ct = new Constraint(modelBuilder);
-    LinearConstraintProto.Builder lin = ct.getBuilder().getLinearBuilder();
-    for (IntVar var : vars) {
-      lin.addVars(var.getIndex());
-    }
-    for (long c : coeffs) {
-      lin.addCoeffs(c);
-    }
-    lin.addDomain(lb);
-    lin.addDomain(ub);
-    return ct;
+  /** Adds {@code left == right}. */
+  public Constraint addEquality(LinearExpr left, LinearExpr right) {
+    return addLinearExpressionInDomain(new Difference(left, right), new Domain(0));
   }
 
-  /** Add {@code lb <= sum(vars[i] * coeffs[i]) <= ub}. */
-  public Constraint addLinearConstraint(IntVar[] vars, int[] coeffs, long lb, long ub) {
-    return addLinearConstraint(vars, toLongArray(coeffs), lb, ub);
+  /** Adds {@code left + offset == right}. */
+  public Constraint addEqualityWithOffset(LinearExpr left, LinearExpr right, long offset) {
+    return addLinearExpressionInDomain(new Difference(left, right), new Domain(-offset));
   }
 
-  /**
-   * Add {@code sum(vars[i] * coeffs[i]) in domain}, where domain is a flattened list of intervals
-   * similar to the one for enumerated integer variables.
-   */
-  public Constraint addLinearExpressionInDomain(IntVar[] vars, long[] coeffs, Domain domain) {
-    Constraint ct = new Constraint(modelBuilder);
-    LinearConstraintProto.Builder lin = ct.getBuilder().getLinearBuilder();
-    for (IntVar var : vars) {
-      lin.addVars(var.getIndex());
-    }
-    for (long c : coeffs) {
-      lin.addCoeffs(c);
-    }
-    for (long b : domain.flattenedIntervals()) {
-      lin.addDomain(b);
-    }
-    return ct;
+  /** Adds {@code expr <= value}. */
+  public Constraint addLessOrEqual(LinearExpr expr, long value) {
+    return addLinearExpressionInDomain(expr, new Domain(Long.MIN_VALUE, value));
   }
 
-  /** Add {@code sum(vars[i] * coeffs[i]) == value}. */
-  public Constraint addLinearExpressionEqual(IntVar[] vars, long[] coeffs, long value) {
-    return addLinearConstraint(vars, coeffs, value, value);
+  /** Adds {@code left <= right}. */
+  public Constraint addLessOrEqual(LinearExpr left, LinearExpr right) {
+    return addLinearExpressionInDomain(new Difference(left, right), 
+                                              new Domain(Long.MIN_VALUE, 0));
   }
 
-  /** Add {@code sum(vars[i] * coeffs[i]) == value}. */
-  public Constraint addLinearExpressionEqual(IntVar[] vars, int[] coeffs, long value) {
-    return addLinearConstraint(vars, toLongArray(coeffs), value, value);
+  /** Adds {@code left + offset <= right}. */
+  public Constraint addLessOrEqualWithOffset(LinearExpr left, LinearExpr right, long offset) {
+    return addLinearExpressionInDomain(new Difference(left, right), 
+                                       new Domain(Long.MIN_VALUE, -offset));
   }
 
-  /** Add {@code sum(vars[i] * coeffs[i]) == target}. */
-  public Constraint addLinearExpressionEqual(IntVar[] vars, long[] coeffs, IntVar target) {
-    int size = vars.length;
-    IntVar[] newVars = new IntVar[size + 1];
-    long[] newCoeffs = new long[size + 1];
-    for (int i = 0; i < size; ++i) {
-      newVars[i] = vars[i];
-      newCoeffs[i] = coeffs[i];
-    }
-    newVars[size] = target;
-    newCoeffs[size] = -1;
-    return addLinearConstraint(newVars, newCoeffs, 0, 0);
+  /** Adds {@code expr >= value}. */
+  public Constraint addGreaterOrEqual(LinearExpr expr, long value) {
+    return addLinearExpressionInDomain(expr, new Domain(value, Long.MAX_VALUE));
   }
 
-  /** Add {@code sum(vars[i] * coeffs[i]) == target}. */
-  public Constraint addLinearExpressionEqual(IntVar[] vars, int[] coeffs, IntVar target) {
-    return addLinearExpressionEqual(vars, toLongArray(coeffs), target);
+  /** Adds {@code left >= right}. */
+  public Constraint addGreaterOrEqual(LinearExpr left, LinearExpr right) {
+    return addLinearExpressionInDomain(new Difference(left, right), new Domain(0, Long.MAX_VALUE));
+  }
+  
+  /** Adds {@code left + offset >= right}. */
+  public Constraint addGreaterOrEqualWithOffset(LinearExpr left, LinearExpr right, long offset) {
+    return addLinearExpressionInDomain(new Difference(left, right), 
+                                       new Domain(-offset, Long.MAX_VALUE));
+  }
+  
+  /** Adds {@code expr != value}. */
+  public Constraint addDifferent(LinearExpr expr, long value) {
+    return addLinearExpressionInDomain(expr, Domain.fromFlatIntervals(
+        new long[] {Long.MIN_VALUE, value - 1, value + 1, Long.MAX_VALUE}));
   }
 
-  /** Adds {@code var <= value}. */
-  public Constraint addLessOrEqual(IntVar var, long value) {
-    Constraint ct = new Constraint(modelBuilder);
-    LinearConstraintProto.Builder lin = ct.getBuilder().getLinearBuilder();
-    lin.addVars(var.getIndex());
-    lin.addCoeffs(1);
-    lin.addDomain(java.lang.Long.MIN_VALUE);
-    lin.addDomain(value);
-    return ct;
+  /** Adds {@code left != right}. */
+  public Constraint addDifferent(IntVar left, IntVar right) {
+    return addLinearExpressionInDomain(new Difference(left, right), Domain.fromFlatIntervals(
+        new long[] {Long.MIN_VALUE, -1, 1, Long.MAX_VALUE}));
   }
 
-  /** Adds {@code before <= after}. */
-  public Constraint addLessOrEqual(IntVar before, IntVar after) {
-    return addLessOrEqualWithOffset(before, after, 0);
-  }
-
-  /** Adds {@code var >= value}. */
-  public Constraint addGreaterOrEqual(IntVar var, long value) {
-    Constraint ct = new Constraint(modelBuilder);
-    LinearConstraintProto.Builder lin = ct.getBuilder().getLinearBuilder();
-    lin.addVars(var.getIndex());
-    lin.addCoeffs(1);
-    lin.addDomain(value);
-    lin.addDomain(java.lang.Long.MAX_VALUE);
-    return ct;
-  }
-
-  /** Adds {@code var == value}. */
-  public Constraint addEquality(IntVar var, long value) {
-    Constraint ct = new Constraint(modelBuilder);
-    LinearConstraintProto.Builder lin = ct.getBuilder().getLinearBuilder();
-    lin.addVars(var.getIndex());
-    lin.addCoeffs(1);
-    lin.addDomain(value);
-    lin.addDomain(value);
-    return ct;
-  }
-
-  /** Adds {@code a == b}. */
-  public Constraint addEquality(IntVar a, IntVar b) {
-    return addEqualityWithOffset(a, b, 0);
-  }
-
-  /** Adds {@code a + offset == b}. */
-  public Constraint addEqualityWithOffset(IntVar a, IntVar b, long offset) {
-    Constraint ct = new Constraint(modelBuilder);
-    LinearConstraintProto.Builder lin = ct.getBuilder().getLinearBuilder();
-    lin.addVars(a.getIndex());
-    lin.addCoeffs(-1);
-    lin.addVars(b.getIndex());
-    lin.addCoeffs(1);
-    lin.addDomain(offset);
-    lin.addDomain(offset);
-    return ct;
-  }
-
-  /** Adds {@code var != value}. */
-  public Constraint addDifferent(IntVar var, long value) {
-    Constraint ct = new Constraint(modelBuilder);
-    LinearConstraintProto.Builder lin = ct.getBuilder().getLinearBuilder();
-    lin.addVars(var.getIndex());
-    lin.addCoeffs(1);
-    if (value > java.lang.Long.MIN_VALUE) {
-      lin.addDomain(java.lang.Long.MIN_VALUE);
-      lin.addDomain(value - 1);
-    }
-    if (value < java.lang.Long.MAX_VALUE) {
-      lin.addDomain(value + 1);
-      lin.addDomain(java.lang.Long.MAX_VALUE);
-    }
-    return ct;
-  }
-
-  /** Adds {@code a != b}. */
-  public Constraint addDifferent(IntVar a, IntVar b) {
-    return addDifferentWithOffset(a, b, 0);
-  }
-
-  /** Adds {@code a + offset != b} */
-  public Constraint addDifferentWithOffset(IntVar a, IntVar b, long offset) {
-    Constraint ct = new Constraint(modelBuilder);
-    LinearConstraintProto.Builder lin = ct.getBuilder().getLinearBuilder();
-    lin.addVars(a.getIndex());
-    lin.addCoeffs(-1);
-    lin.addVars(b.getIndex());
-    lin.addCoeffs(1);
-    if (offset > java.lang.Long.MIN_VALUE) {
-      lin.addDomain(java.lang.Long.MIN_VALUE);
-      lin.addDomain(offset - 1);
-    }
-    if (offset < java.lang.Long.MAX_VALUE) {
-      lin.addDomain(offset + 1);
-      lin.addDomain(java.lang.Long.MAX_VALUE);
-    }
-    return ct;
-  }
-
-  /** Adds {@code before + offset <= after}. */
-  public Constraint addLessOrEqualWithOffset(IntVar before, IntVar after, long offset) {
-    Constraint ct = new Constraint(modelBuilder);
-    LinearConstraintProto.Builder lin = ct.getBuilder().getLinearBuilder();
-    lin.addVars(before.getIndex());
-    lin.addCoeffs(-1);
-    lin.addVars(after.getIndex());
-    lin.addCoeffs(1);
-    lin.addDomain(offset);
-    lin.addDomain(java.lang.Long.MAX_VALUE);
-    return ct;
+  /** Adds {@code left + offset != right}. */
+  public Constraint addDifferentWithOffset(IntVar left, IntVar right, long offset) {
+    return addLinearExpressionInDomain(new Difference(left, right), Domain.fromFlatIntervals(
+        new long[] {Long.MIN_VALUE, -offset - 1, -offset + 1, Long.MAX_VALUE}));
   }
 
   // Integer constraints.
@@ -1074,73 +934,25 @@ public class CpModel {
 
   // Objective.
 
-  /** Adds a minimization objective of a single variable. */
-  public void minimize(IntVar var) {
+  /** Adds a minimization objective of a linear expression. */
+  public void minimize(LinearExpr expr) {
     CpObjectiveProto.Builder obj = modelBuilder.getObjectiveBuilder();
-    obj.addVars(var.getIndex());
-    obj.addCoeffs(1);
-  }
-
-  /** Adds a minimization objective of a sum of variables. */
-  public void minimizeSum(IntVar[] vars) {
-    CpObjectiveProto.Builder obj = modelBuilder.getObjectiveBuilder();
-    for (IntVar var : vars) {
-      obj.addVars(var.getIndex());
-      obj.addCoeffs(1);
+    for (int i = 0; i < expr.numElements(); ++i) {
+      obj.addVars(expr.getVariable(i).getIndex());
+      obj.addCoeffs(expr.getCoefficient(i));
     }
   }
 
-  /** Adds a minimization objective of a scalar product of variables. */
-  public void minimizeLinearExpression(IntVar[] vars, long[] coeffs) {
+  /** Adds a maximization objective of a linear expression. */
+  public void maximize(LinearExpr expr) {
     CpObjectiveProto.Builder obj = modelBuilder.getObjectiveBuilder();
-    for (IntVar var : vars) {
-      obj.addVars(var.getIndex());
-    }
-    for (long c : coeffs) {
-      obj.addCoeffs(c);
-    }
-  }
-
-  /** Adds a minimization objective of a scalar product of variables. */
-  public void minimizeLinearExpression(IntVar[] vars, int[] coeffs) {
-    minimizeLinearExpression(vars, toLongArray(coeffs));
-  }
-
-  /** Adds a maximization objective of a single variable. */
-  public void maximize(IntVar var) {
-    CpObjectiveProto.Builder obj = modelBuilder.getObjectiveBuilder();
-    obj.addVars(negated(var.getIndex()));
-    obj.addCoeffs(1);
-    obj.setScalingFactor(-1.0);
-  }
-
-  /** Adds a maximization objective of a sum of variables. */
-  public void maximizeSum(IntVar[] vars) {
-    CpObjectiveProto.Builder obj = modelBuilder.getObjectiveBuilder();
-    for (IntVar var : vars) {
-      obj.addVars(negated(var.getIndex()));
-      obj.addCoeffs(1);
+    for (int i = 0; i < expr.numElements(); ++i) {
+      obj.addVars(expr.getVariable(i).getIndex());
+      obj.addCoeffs(-expr.getCoefficient(i));
     }
     obj.setScalingFactor(-1.0);
   }
 
-  /** Adds a maximization objective of a scalar product of variables. */
-  public void maximizeLinearExpression(IntVar[] vars, long[] coeffs) {
-    CpObjectiveProto.Builder obj = modelBuilder.getObjectiveBuilder();
-    for (IntVar var : vars) {
-      obj.addVars(negated(var.getIndex()));
-    }
-    for (long c : coeffs) {
-      obj.addCoeffs(c);
-    }
-    obj.setScalingFactor(-1.0);
-  }
-
-  /** Adds a maximization objective of a scalar product of variables. */
-  public void maximizeLinearExpression(IntVar[] vars, int[] coeffs) {
-    maximizeLinearExpression(vars, toLongArray(coeffs));
-  }
-
   // DecisionStrategy
 
   /** Adds {@code DecisionStrategy(variables, varStr, domStr)}. */

ortools/com/google/ortools/sat/Difference.java

@@ -0,0 +1,45 @@
+// Copyright 2010-2018 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;
+
+/** the substraction of two linear expressions. Used internally. */
+class Difference implements LinearExpr {
+  private LinearExpr left;
+  private LinearExpr right;
+
+  public Difference(LinearExpr left, LinearExpr right) {
+    this.left = left;
+    this.right = right;
+  }
+
+  public int numElements() {
+    return left.numElements() + right.numElements();
+  }
+
+  public IntVar getVariable(int index) {
+    if (index < left.numElements()) {
+      return left.getVariable(index);
+    } else {
+      return right.getVariable(index - left.numElements());
+    }
+  }
+
+  public long getCoefficient(int index) {
+    if (index < left.numElements()) {
+      return left.getCoefficient(index);
+    } else {
+      return -right.getCoefficient(index - left.numElements());
+    }
+  }
+}

ortools/com/google/ortools/sat/IntVar.java

@@ -17,7 +17,7 @@ import com.google.ortools.sat.CpModelProto;
 import com.google.ortools.sat.IntegerVariableProto;
 
 /** An integer variable. */
-public class IntVar implements Literal {
+public class IntVar implements Literal, LinearExpr {
   IntVar(CpModelProto.Builder builder, Domain domain, String name) {
     this.modelBuilder = builder;
     this.variableIndex = modelBuilder.getVariablesCount();
@@ -50,6 +50,21 @@ public class IntVar implements Literal {
     return varBuilder;
   }
 
+  // LinearExpr interface.
+  public int numElements() {
+    return 1;
+  }
+
+  public IntVar getVariable(int index) {
+    assert(index == 0);
+    return this;
+  }
+
+  public long getCoefficient(int index) {
+    assert(index == 0);
+    return 1;
+  }
+
   /** Returns a short string describing the variable. */
   @Override
   public String getShortString() {

ortools/com/google/ortools/sat/LinearExpr.java

@@ -0,0 +1,46 @@
+// Copyright 2010-2018 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;
+
+/** A linear expression interface that can be parsed. */
+public interface LinearExpr {
+  /** Returns the number of elements in the interface. */
+  int numElements();
+
+  /** Returns the ith variable. */
+  IntVar getVariable(int index);
+
+  /** Returns the ith coefficient. */
+  long getCoefficient(int index);
+
+  /** Creates a sum expression. */
+  static LinearExpr Sum(IntVar[] variables) {
+    return new SumOfVariables(variables);
+  }
+
+  /** Creates a scalar product. */
+  static LinearExpr ScalProd(IntVar[] variables, long[] coefficients) {
+    return new ScalProd(variables, coefficients);
+  }
+
+  /** Creates a scalar product. */
+  static LinearExpr ScalProd(IntVar[] variables, int[] coefficients) {
+    long[] tmp = new long[coefficients.length];
+    for (int i = 0; i < coefficients.length; ++i) {
+      tmp[i] = coefficients[i];
+    }
+    return new ScalProd(variables, tmp);
+  }
+
+}

ortools/com/google/ortools/sat/ScalProd.java

@@ -0,0 +1,37 @@
+// Copyright 2010-2018 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;
+
+/** A linear expression interface that can be parsed. */
+public class ScalProd implements LinearExpr {
+  private IntVar[] variables;
+  private long[] coefficients;
+
+  public ScalProd(IntVar[] variables, long[] coefficients) {
+    this.variables = variables;
+    this.coefficients = coefficients;
+  }
+
+  public int numElements() {
+    return variables.length;
+  }
+
+  public IntVar getVariable(int index) {
+    return variables[index];
+  }
+
+  public long getCoefficient(int index) {
+    return coefficients[index];
+  }
+}

ortools/com/google/ortools/sat/SumOfVariables.java

@@ -0,0 +1,35 @@
+// Copyright 2010-2018 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;
+
+/** A linear expression interface that can be parsed. */
+public class SumOfVariables implements LinearExpr {
+  private IntVar[] variables;
+
+  public SumOfVariables(IntVar[] variables) {
+    this.variables = variables;
+  }
+
+  public int numElements() {
+    return variables.length;
+  }
+
+  public IntVar getVariable(int index) {
+    return variables[index];
+  }
+
+  public long getCoefficient(int index) {
+    return 1;
+  }
+}

ortools/sat/samples/BinPackingProblemSat.java

@@ -15,6 +15,7 @@ import com.google.ortools.sat.CpModel;
 import com.google.ortools.sat.CpSolver;
 import com.google.ortools.sat.CpSolverStatus;
 import com.google.ortools.sat.IntVar;
+import com.google.ortools.sat.LinearExpr;
 
 /** Solves a bin packing problem with the CP-SAT solver. */
 public class BinPackingProblemSat {
@@ -65,7 +66,7 @@ public class BinPackingProblemSat {
       for (int i = 0; i < numItems; ++i) {
         vars[i] = x[i][b];
       }
-      model.addLinearExpressionEqual(vars, sizes, load[b]);
+      model.addEquality(LinearExpr.ScalProd(vars, sizes), load[b]);
     }
 
     // Place all items.
@@ -74,7 +75,7 @@ public class BinPackingProblemSat {
       for (int b = 0; b < numBins; ++b) {
         vars[b] = x[i][b];
       }
-      model.addSumEqual(vars, items[i][1]);
+      model.addEquality(LinearExpr.Sum(vars), items[i][1]);
     }
 
     // Links load and slack.
@@ -87,7 +88,7 @@ public class BinPackingProblemSat {
     }
 
     // Maximize sum of slacks.
-    model.maximizeSum(slacks);
+    model.maximize(LinearExpr.Sum(slacks));
 
     // Solves and prints out the solution.
     CpSolver solver = new CpSolver();

ortools/sat/samples/ChannelingSampleSat.java

@@ -16,6 +16,7 @@ import com.google.ortools.sat.CpSolver;
 import com.google.ortools.sat.CpSolverSolutionCallback;
 import com.google.ortools.sat.DecisionStrategyProto;
 import com.google.ortools.sat.IntVar;
+import com.google.ortools.sat.LinearExpr;
 import com.google.ortools.sat.SatParameters;
 
 /** Link integer constraints together. */
@@ -41,7 +42,7 @@ public class ChannelingSampleSat {
 
     // Create our two half-reified constraints.
     // First, b implies (y == 10 - x).
-    model.addSumEqual(new IntVar[] {x, y}, 10).onlyEnforceIf(b);
+    model.addEquality(LinearExpr.Sum(new IntVar[] {x, y}), 10).onlyEnforceIf(b);
     // Second, not(b) implies y == 0.
     model.addEquality(y, 0).onlyEnforceIf(b.not());
 

ortools/sat/samples/CpIsFunSat.java

@@ -16,6 +16,7 @@ import com.google.ortools.sat.CpModel;
 import com.google.ortools.sat.CpSolver;
 import com.google.ortools.sat.CpSolverSolutionCallback;
 import com.google.ortools.sat.IntVar;
+import com.google.ortools.sat.LinearExpr;
 
 /** Cryptarithmetic puzzle. */
 public class CpIsFunSat {
@@ -73,9 +74,9 @@ public class CpIsFunSat {
     model.addAllDifferent(letters);
 
     // CP + IS + FUN = TRUE
-    model.addLinearExpressionEqual(new IntVar[] {c, p, i, s, f, u, n, t, r, u, e},
+    model.addEquality(LinearExpr.ScalProd(new IntVar[] {c, p, i, s, f, u, n, t, r, u, e},
         new long[] {
-            base, 1, base, 1, base * base, base, 1, -base * base * base, -base * base, -base, -1},
+            base, 1, base, 1, base * base, base, 1, -base * base * base, -base * base, -base, -1}),
         0);
     // [END constraints]
 

ortools/sat/samples/EarlinessTardinessCostSampleSat.java

@@ -16,6 +16,7 @@ import com.google.ortools.sat.CpSolver;
 import com.google.ortools.sat.CpSolverSolutionCallback;
 import com.google.ortools.sat.DecisionStrategyProto;
 import com.google.ortools.sat.IntVar;
+import com.google.ortools.sat.LinearExpr;
 import com.google.ortools.sat.SatParameters;
 
 /** Encode the piecewise linear expression. */
@@ -47,16 +48,18 @@ public class EarlinessTardinessCostSampleSat {
 
     // First segment: s1 == earlinessCost * (earlinessDate - x).
     IntVar s1 = model.newIntVar(-largeConstant, largeConstant, "s1");
-    model.addLinearExpressionEqual(
-        new IntVar[] {s1, x}, new long[] {1, earlinessCost}, earlinessCost* earlinessDate);
+    model.addEquality(
+        LinearExpr.ScalProd(new IntVar[] {s1, x}, new long[] {1, earlinessCost}),
+        earlinessCost* earlinessDate);
 
     // Second segment.
     IntVar s2 = model.newConstant(0);
 
     // Third segment: s3 == latenessCost * (x - latenessDate).
     IntVar s3 = model.newIntVar(-largeConstant, largeConstant, "s3");
-    model.addLinearExpressionEqual(
-        new IntVar[] {s3, x}, new long[] {1, -latenessCost}, -latenessCost* latenessDate);
+    model.addEquality(
+        LinearExpr.ScalProd(new IntVar[] {s3, x}, new long[] {1, -latenessCost}),
+        -latenessCost* latenessDate);
 
     // Link together expr and x through s1, s2, and s3.
     model.addMaxEquality(expr, new IntVar[] {s1, s2, s3});

ortools/sat/samples/RabbitsAndPheasantsSat.java

@@ -15,6 +15,7 @@ import com.google.ortools.sat.CpModel;
 import com.google.ortools.sat.CpSolver;
 import com.google.ortools.sat.CpSolverStatus;
 import com.google.ortools.sat.IntVar;
+import com.google.ortools.sat.LinearExpr;
 
 /**
  * In a field of rabbits and pheasants, there are 20 heads and 56 legs. How many rabbits and
@@ -32,9 +33,9 @@ public class RabbitsAndPheasantsSat {
     IntVar r = model.newIntVar(0, 100, "r");
     IntVar p = model.newIntVar(0, 100, "p");
     // 20 heads.
-    model.addSumEqual(new IntVar[] {r, p}, 20);
+    model.addEquality(LinearExpr.Sum(new IntVar[] {r, p}), 20);
     // 56 legs.
-    model.addLinearExpressionEqual(new IntVar[] {r, p}, new long[] {4, 2}, 56);
+    model.addEquality(LinearExpr.ScalProd(new IntVar[] {r, p}, new long[] {4, 2}), 56);
 
     // Creates a solver and solves the model.
     CpSolver solver = new CpSolver();

ortools/sat/samples/RankingSampleSat.java

@@ -15,6 +15,7 @@ import com.google.ortools.sat.CpModel;
 import com.google.ortools.sat.CpSolver;
 import com.google.ortools.sat.CpSolverStatus;
 import com.google.ortools.sat.IntVar;
+import com.google.ortools.sat.LinearExpr;
 import com.google.ortools.sat.IntervalVar;
 import com.google.ortools.sat.Literal;
 import java.util.ArrayList;
@@ -89,7 +90,7 @@ public class RankingSampleSat {
       vars[numTasks] = ranks[i];
       coefs[numTasks] = -1;
       // ranks == sum(precedences) - 1;
-      model.addLinearExpressionEqual(vars, coefs, 1);
+      model.addEquality(LinearExpr.ScalProd(vars, coefs), 1);
     }
   }
 
@@ -153,7 +154,7 @@ public class RankingSampleSat {
     }
     objectiveVars[numTasks] = makespan;
     objectiveCoefs[numTasks] = 2;
-    model.minimizeLinearExpression(objectiveVars, objectiveCoefs);
+    model.minimize(LinearExpr.ScalProd(objectiveVars, objectiveCoefs));
 
     // Creates a solver and solves the model.
     CpSolver solver = new CpSolver();

ortools/sat/samples/SolveAndPrintIntermediateSolutionsSampleSat.java

@@ -70,7 +70,7 @@ public class SolveAndPrintIntermediateSolutionsSampleSat {
 
     // Maximize a linear combination of variables.
     // [START objective]
-    model.maximizeLinearExpression(new IntVar[] {x, y, z}, new int[] {1, 2, 3});
+    model.maximize(LinearExpr.ScalProd(new IntVar[] {x, y, z}, new int[] {1, 2, 3}));
     // [END objective]
 
     // Create a solver and solve the model.

ortools/sat/samples/StepFunctionSampleSat.java

@@ -46,16 +46,14 @@ public class StepFunctionSampleSat {
 
     // expr == 0 on [5, 6] U [8, 10]
     Literal b0 = model.newBoolVar("b0");
-    model.addSumInDomain(new IntVar[] {x}, Domain.fromValues(new long[] {5, 6, 8, 9, 10}))
-        .onlyEnforceIf(b0);
+    model.addLinearExpressionInDomain(
+        x, Domain.fromValues(new long[] {5, 6, 8, 9, 10})).onlyEnforceIf(b0);
     model.addEquality(expr, 0).onlyEnforceIf(b0);
 
     // expr == 2 on [0, 1] U [3, 4] U [11, 20]
     Literal b2 = model.newBoolVar("b2");
-    model
-        .addSumInDomain(
-            new IntVar[] {x}, Domain.fromIntervals(new long[][] {{0, 1}, {3, 4}, {11, 20}}))
-        .onlyEnforceIf(b2);
+    model.addLinearExpressionInDomain(
+        x, Domain.fromIntervals(new long[][] {{0, 1}, {3, 4}, {11, 20}})).onlyEnforceIf(b2);
     model.addEquality(expr, 2).onlyEnforceIf(b2);
 
     // expr == 3 when x = 7