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AssignmentGroupsMip.java
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AssignmentGroupsMip.java
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// Copyright 2010-2024 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 AssignmentGroupsMip {
public static void main(String[] args) {
Loader.loadNativeLibraries();
// Data
// [START data]
double[][] costs = {
{90, 76, 75, 70, 50, 74},
{35, 85, 55, 65, 48, 101},
{125, 95, 90, 105, 59, 120},
{45, 110, 95, 115, 104, 83},
{60, 105, 80, 75, 59, 62},
{45, 65, 110, 95, 47, 31},
{38, 51, 107, 41, 69, 99},
{47, 85, 57, 71, 92, 77},
{39, 63, 97, 49, 118, 56},
{47, 101, 71, 60, 88, 109},
{17, 39, 103, 64, 61, 92},
{101, 45, 83, 59, 92, 27},
};
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();
// [END data]
// Allowed groups of workers:
// [START allowed_groups]
int[][] group1 = {
// group of worker 0-3
{2, 3},
{1, 3},
{1, 2},
{0, 1},
{0, 2},
};
int[][] group2 = {
// group of worker 4-7
{6, 7},
{5, 7},
{5, 6},
{4, 5},
{4, 7},
};
int[][] group3 = {
// group of worker 8-11
{10, 11},
{9, 11},
{9, 10},
{8, 10},
{8, 11},
};
// [END allowed_groups]
// 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 one task.
for (int worker : allWorkers) {
MPConstraint constraint = solver.makeConstraint(0, 1, "");
for (int task : allTasks) {
constraint.setCoefficient(x[worker][task], 1);
}
}
// 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]
// [START assignments]
// Create variables for each worker, indicating whether they work on some task.
MPVariable[] work = new MPVariable[numWorkers];
for (int worker : allWorkers) {
work[worker] = solver.makeBoolVar("work[" + worker + "]");
}
for (int worker : allWorkers) {
// MPVariable[] vars = new MPVariable[numTasks];
MPConstraint constraint = solver.makeConstraint(0, 0, "");
for (int task : allTasks) {
// vars[task] = x[worker][task];
constraint.setCoefficient(x[worker][task], 1);
}
// solver.addEquality(work[worker], LinearExpr.sum(vars));
constraint.setCoefficient(work[worker], -1);
}
// Group1
MPConstraint constraintG1 = solver.makeConstraint(1, 1, "");
for (int i = 0; i < group1.length; ++i) {
// a*b can be transformed into 0 <= a + b - 2*p <= 1 with p in [0,1]
// p is True if a AND b, False otherwise
MPConstraint constraint = solver.makeConstraint(0, 1, "");
constraint.setCoefficient(work[group1[i][0]], 1);
constraint.setCoefficient(work[group1[i][1]], 1);
MPVariable p = solver.makeBoolVar("g1_p" + i);
constraint.setCoefficient(p, -2);
constraintG1.setCoefficient(p, 1);
}
// Group2
MPConstraint constraintG2 = solver.makeConstraint(1, 1, "");
for (int i = 0; i < group2.length; ++i) {
// a*b can be transformed into 0 <= a + b - 2*p <= 1 with p in [0,1]
// p is True if a AND b, False otherwise
MPConstraint constraint = solver.makeConstraint(0, 1, "");
constraint.setCoefficient(work[group2[i][0]], 1);
constraint.setCoefficient(work[group2[i][1]], 1);
MPVariable p = solver.makeBoolVar("g2_p" + i);
constraint.setCoefficient(p, -2);
constraintG2.setCoefficient(p, 1);
}
// Group3
MPConstraint constraintG3 = solver.makeConstraint(1, 1, "");
for (int i = 0; i < group3.length; ++i) {
// a*b can be transformed into 0 <= a + b - 2*p <= 1 with p in [0,1]
// p is True if a AND b, False otherwise
MPConstraint constraint = solver.makeConstraint(0, 1, "");
constraint.setCoefficient(work[group3[i][0]], 1);
constraint.setCoefficient(work[group3[i][1]], 1);
MPVariable p = solver.makeBoolVar("g3_p" + i);
constraint.setCoefficient(p, -2);
constraintG3.setCoefficient(p, 1);
}
// [END assignments]
// 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 AssignmentGroupsMip() {}
}
// [END program]