Port AssignmentTaskSizeMip to all languages

ortools/linear_solver/samples/AssignmentTaskSizesMip.java

@@ -0,0 +1,134 @@
+// 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.
+
+// [START program]
+package com.google.ortools.linearsolver.samples;
+// [START import]
+import com.google.ortools.Loader;
+import com.google.ortools.linearsolver.MPConstraint;
+import com.google.ortools.linearsolver.MPObjective;
+import com.google.ortools.linearsolver.MPSolver;
+import com.google.ortools.linearsolver.MPVariable;
+import java.util.stream.IntStream;
+// [END import]
+
+/** MIP example that solves an assignment problem. */
+public class AssignmentTaskSizesMip {
+  public static void main(String[] args) {
+    Loader.loadNativeLibraries();
+    // Data
+    // [START data]
+    double[][] costs = {
+        {90, 76, 75, 70, 50, 74, 12, 68},
+        {35, 85, 55, 65, 48, 101, 70, 83},
+        {125, 95, 90, 105, 59, 120, 36, 73},
+        {45, 110, 95, 115, 104, 83, 37, 71},
+        {60, 105, 80, 75, 59, 62, 93, 88},
+        {45, 65, 110, 95, 47, 31, 81, 34},
+        {38, 51, 107, 41, 69, 99, 115, 48},
+        {47, 85, 57, 71, 92, 77, 109, 36},
+        {39, 63, 97, 49, 118, 56, 92, 61},
+        {47, 101, 71, 60, 88, 109, 52, 90},
+    };
+    int numWorkers = costs.length;
+    int numTasks = costs[0].length;
+
+    final int[] allWorkers = IntStream.range(0, numWorkers).toArray();
+    final int[] allTasks = IntStream.range(0, numTasks).toArray();
+
+    final int[] taskSizes = {10, 7, 3, 12, 15, 4, 11, 5};
+    // Maximum total of task sizes for any worker
+    final int totalSizeMax = 15;
+    // [END data]
+
+    // Solver
+    // [START solver]
+    // Create the linear solver with the SCIP backend.
+    MPSolver solver = MPSolver.createSolver("SCIP");
+    if (solver == null) {
+      System.out.println("Could not create solver SCIP");
+      return;
+    }
+    // [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 worker : allWorkers) {
+      for (int task : allTasks) {
+        x[worker][task] = solver.makeBoolVar("x["+worker+","+task+"]");
+      }
+    }
+    // [END variables]
+
+    // Constraints
+    // [START constraints]
+    // Each worker is assigned to at most max task size.
+    for (int worker : allWorkers) {
+      MPConstraint constraint = solver.makeConstraint(0, totalSizeMax, "");
+      for (int task : allTasks) {
+        constraint.setCoefficient(x[worker][task], taskSizes[task]);
+      }
+    }
+    // Each task is assigned to exactly one worker.
+    for (int task : allTasks) {
+      MPConstraint constraint = solver.makeConstraint(1, 1, "");
+      for (int worker : allWorkers) {
+        constraint.setCoefficient(x[worker][task], 1);
+      }
+    }
+    // [END constraints]
+
+    // Objective
+    // [START objective]
+    MPObjective objective = solver.objective();
+    for (int worker : allWorkers) {
+      for (int task : allTasks) {
+        objective.setCoefficient(x[worker][task], costs[worker][task]);
+      }
+    }
+    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 worker : allWorkers) {
+        for (int task : allTasks) {
+          // Test if x[i][j] is 0 or 1 (with tolerance for floating point
+          // arithmetic).
+          if (x[worker][task].solutionValue() > 0.5) {
+            System.out.println(
+                "Worker " + worker + " assigned to task " + task + ".  Cost: " + costs[worker][task]);
+          }
+        }
+      }
+    } else {
+      System.err.println("No solution found.");
+    }
+    // [END print_solution]
+  }
+
+  private AssignmentTaskSizesMip() {}
+}
+// [END program]