// Copyright 2010-2025 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] // Solve a simple assignment problem. // [START import] #include #include #include #include #include "absl/base/log_severity.h" #include "absl/log/globals.h" #include "absl/strings/str_format.h" #include "ortools/base/init_google.h" #include "ortools/base/logging.h" #include "ortools/linear_solver/linear_solver.h" // [END import] namespace operations_research { void AssignmentTeamsMip() { // Data // [START data] const std::vector> costs = {{ {{90, 76, 75, 70}}, {{35, 85, 55, 65}}, {{125, 95, 90, 105}}, {{45, 110, 95, 115}}, {{60, 105, 80, 75}}, {{45, 65, 110, 95}}, }}; const int num_workers = costs.size(); std::vector all_workers(num_workers); std::iota(all_workers.begin(), all_workers.end(), 0); const int num_tasks = costs[0].size(); std::vector all_tasks(num_tasks); std::iota(all_tasks.begin(), all_tasks.end(), 0); const std::vector team1 = {{0, 2, 4}}; const std::vector team2 = {{1, 3, 5}}; // Maximum total of tasks for any team const int team_max = 2; // [END data] // Solver // [START solver] // Create the mip solver with the SCIP backend. std::unique_ptr solver(MPSolver::CreateSolver("SCIP")); if (!solver) { LOG(WARNING) << "SCIP solver unavailable."; 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. std::vector> x( num_workers, std::vector(num_tasks)); for (int worker : all_workers) { for (int task : all_tasks) { x[worker][task] = solver->MakeBoolVar(absl::StrFormat("x[%d,%d]", worker, task)); } } // [END variables] // Constraints // [START constraints] // Each worker is assigned to at most one task. for (int worker : all_workers) { LinearExpr worker_sum; for (int task : all_tasks) { worker_sum += x[worker][task]; } solver->MakeRowConstraint(worker_sum <= 1.0); } // Each task is assigned to exactly one worker. for (int task : all_tasks) { LinearExpr task_sum; for (int worker : all_workers) { task_sum += x[worker][task]; } solver->MakeRowConstraint(task_sum == 1.0); } // Each team takes at most two tasks. LinearExpr team1_tasks; for (int worker : team1) { for (int task : all_tasks) { team1_tasks += x[worker][task]; } } solver->MakeRowConstraint(team1_tasks <= team_max); LinearExpr team2_tasks; for (int worker : team2) { for (int task : all_tasks) { team2_tasks += x[worker][task]; } } solver->MakeRowConstraint(team2_tasks <= team_max); // [END constraints] // Objective. // [START objective] MPObjective* const objective = solver->MutableObjective(); for (int worker : all_workers) { for (int task : all_tasks) { objective->SetCoefficient(x[worker][task], costs[worker][task]); } } objective->SetMinimization(); // [END objective] // Solve // [START solve] const MPSolver::ResultStatus result_status = solver->Solve(); // [END solve] // Print solution. // [START print_solution] // Check that the problem has a feasible solution. if (result_status != MPSolver::OPTIMAL && result_status != MPSolver::FEASIBLE) { LOG(FATAL) << "No solution found."; } LOG(INFO) << "Total cost = " << objective->Value() << "\n\n"; for (int worker : all_workers) { for (int task : all_tasks) { // Test if x[i][j] is 0 or 1 (with tolerance for floating point // arithmetic). if (x[worker][task]->solution_value() > 0.5) { LOG(INFO) << "Worker " << worker << " assigned to task " << task << ". Cost: " << costs[worker][task]; } } } // [END print_solution] } } // namespace operations_research int main(int argc, char* argv[]) { InitGoogle(argv[0], &argc, &argv, true); absl::SetStderrThreshold(absl::LogSeverityAtLeast::kInfo); operations_research::AssignmentTeamsMip(); return EXIT_SUCCESS; } // [END program]