#!/usr/bin/env python3 # 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] """Solves an assignment problem for given group of workers.""" # [START import] from ortools.sat.python import cp_model # [END import] def main() -> None: # Data # [START data] 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], ] num_workers = len(costs) num_tasks = len(costs[0]) # [END data] # Allowed groups of workers: # [START allowed_groups] group1 = [ [0, 0, 1, 1], # Workers 2, 3 [0, 1, 0, 1], # Workers 1, 3 [0, 1, 1, 0], # Workers 1, 2 [1, 1, 0, 0], # Workers 0, 1 [1, 0, 1, 0], # Workers 0, 2 ] group2 = [ [0, 0, 1, 1], # Workers 6, 7 [0, 1, 0, 1], # Workers 5, 7 [0, 1, 1, 0], # Workers 5, 6 [1, 1, 0, 0], # Workers 4, 5 [1, 0, 0, 1], # Workers 4, 7 ] group3 = [ [0, 0, 1, 1], # Workers 10, 11 [0, 1, 0, 1], # Workers 9, 11 [0, 1, 1, 0], # Workers 9, 10 [1, 0, 1, 0], # Workers 8, 10 [1, 0, 0, 1], # Workers 8, 11 ] # [END allowed_groups] # Model # [START model] model = cp_model.CpModel() # [END model] # Variables # [START variables] x = {} for worker in range(num_workers): for task in range(num_tasks): x[worker, task] = model.new_bool_var(f"x[{worker},{task}]") # [END variables] # Constraints # [START constraints] # Each worker is assigned to at most one task. for worker in range(num_workers): model.add_at_most_one(x[worker, task] for task in range(num_tasks)) # Each task is assigned to exactly one worker. for task in range(num_tasks): model.add_exactly_one(x[worker, task] for worker in range(num_workers)) # [END constraints] # [START assignments] # Create variables for each worker, indicating whether they work on some task. work = {} for worker in range(num_workers): work[worker] = model.new_bool_var(f"work[{worker}]") for worker in range(num_workers): for task in range(num_tasks): model.add(work[worker] == sum(x[worker, task] for task in range(num_tasks))) # Define the allowed groups of worders model.add_allowed_assignments([work[0], work[1], work[2], work[3]], group1) model.add_allowed_assignments([work[4], work[5], work[6], work[7]], group2) model.add_allowed_assignments([work[8], work[9], work[10], work[11]], group3) # [END assignments] # Objective # [START objective] objective_terms = [] for worker in range(num_workers): for task in range(num_tasks): objective_terms.append(costs[worker][task] * x[worker, task]) model.minimize(sum(objective_terms)) # [END objective] # Solve # [START solve] solver = cp_model.CpSolver() status = solver.solve(model) # [END solve] # Print solution. # [START print_solution] if status == cp_model.OPTIMAL or status == cp_model.FEASIBLE: print(f"Total cost = {solver.objective_value}\n") for worker in range(num_workers): for task in range(num_tasks): if solver.boolean_value(x[worker, task]): print( f"Worker {worker} assigned to task {task}." + f" Cost = {costs[worker][task]}" ) else: print("No solution found.") # [END print_solution] if __name__ == "__main__": main() # [END program]