51 lines
1.4 KiB
Python
51 lines
1.4 KiB
Python
"""Solves a simple assignment problem."""
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from ortools.sat.python import cp_model
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def main() -> None:
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# Data
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costs = [10,5,8,10,5,2,1]
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num_workers = 2
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deadline = 20
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num_tasks = len(costs)
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# Model
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model = cp_model.CpModel()
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# Variables
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x = {}
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for worker in range(num_workers):
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for task in range(num_tasks):
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x[worker, task] = model.new_bool_var(f"x[{worker},{task}]")
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# Each task is assigned to exactly one worker.
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for task in range(num_tasks):
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model.add_exactly_one(x[worker, task] for worker in range(num_workers))
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# Objective
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for worker in range(num_workers):
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objective_terms = []
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for task in range(num_tasks):
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objective_terms.append(costs[task] * x[worker, task])
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model.AddLinearConstraint(sum(objective_terms), 0, deadline)
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# Solve
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solver = cp_model.CpSolver()
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status = solver.solve(model)
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# Print solution.
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if status == cp_model.OPTIMAL or status == cp_model.FEASIBLE:
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print(f"Total cost = {solver.objective_value}\n")
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for worker in range(num_workers):
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for task in range(num_tasks):
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if solver.boolean_value(x[worker, task]):
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print(
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f"Worker {worker} assigned to task {task}."
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+ f" Cost = {costs[task]}"
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)
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else:
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print("No solution found.")
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if __name__ == "__main__":
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main()
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