Add AssignmentMIP samples

ortools/linear_solver/samples/AssignmentMip.java

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+// 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.
+
+// [START program]
+package com.google.ortools.linearsolver.samples;
+// [START import]
+import com.google.ortools.linearsolver.MPConstraint;
+import com.google.ortools.linearsolver.MPObjective;
+import com.google.ortools.linearsolver.MPSolver;
+import com.google.ortools.linearsolver.MPVariable;
+// [END import]
+
+/** MIP example that solves an assignment problem. */
+public class AssignmentMip {
+  static {
+    System.loadLibrary("jniortools");
+  }
+
+  public static void main(String[] args) {
+    // Data
+    // [START data_model]
+    double[][] costs = {
+        {90, 80, 75, 70},
+        {35, 85, 55, 65},
+        {125, 95, 90, 95},
+        {45, 110, 95, 115},
+        {50, 100, 90, 100},
+    };
+    int numWorkers = costs.length;
+    int numTasks = costs[0].length;
+    // [END data_model]
+
+    // Solver
+    // [START solver]
+    // Create the linear solver with the CBC backend.
+    MPSolver solver = new MPSolver(
+        "AssignmentMip", MPSolver.OptimizationProblemType.CBC_MIXED_INTEGER_PROGRAMMING);
+    // [END solver]
+
+    // Variables
+    // [START variables]
+    // x[i][j] is an array of 0-1 variables, which will be 1
+    // if worker i is assigned to task j.
+    MPVariable[][] x = new MPVariable[numWorkers][numTasks];
+    for (int i = 0; i < numWorkers; ++i) {
+      for (int j = 0; j < numTasks; ++j) {
+        x[i][j] = solver.makeIntVar(0, 1, "");
+      }
+    }
+    // [END variables]
+
+    // Constraints
+    // [START constraints]
+    // Each worker is assigned to at most one task.
+    for (int i = 0; i < numWorkers; ++i) {
+      MPConstraint constraint = solver.makeConstraint(0, 1, "");
+      for (int j = 0; j < numTasks; ++j) {
+        constraint.setCoefficient(x[i][j], 1);
+      }
+    }
+    // Each task is assigned to exactly one worker.
+    for (int j = 0; j < numTasks; ++j) {
+      MPConstraint constraint = solver.makeConstraint(1, 1, "");
+      for (int i = 0; i < numWorkers; ++i) {
+        constraint.setCoefficient(x[i][j], 1);
+      }
+    }
+    // [END constraints]
+
+    // Objective
+    // [START objective]
+    MPObjective objective = solver.objective();
+    for (int i = 0; i < numWorkers; ++i) {
+      for (int j = 0; j < numTasks; ++j) {
+        objective.setCoefficient(x[i][j], costs[i][j]);
+      }
+    }
+    objective.setMinimization();
+    // [END objective]
+
+    // Solve
+    // [START solve]
+    MPSolver.ResultStatus resultStatus = solver.solve();
+    // [END solve]
+
+    // Print solution.
+    // [START print_solution]
+    // Check that the problem has a feasible solution.
+    if (resultStatus == MPSolver.ResultStatus.OPTIMAL
+        || resultStatus == MPSolver.ResultStatus.FEASIBLE) {
+      System.out.println("Total cost: " + objective.value() + "\n");
+      for (int i = 0; i < numWorkers; ++i) {
+        for (int j = 0; j < numTasks; ++j) {
+          // Test if x[i][j] is 0 or 1 (with tolerance for floating point
+          // arithmetic).
+          if (x[i][j].solutionValue() > 0.5) {
+            System.out.println(
+                "Worker " + i + " assigned to task " + j + ".  Cost = " + costs[i][j]);
+          }
+        }
+      }
+    } else {
+      System.err.println("No solution found.");
+    }
+    // [END print_solution]
+  }
+
+  private AssignmentMip() {}
+}
+// [END program]