def test_multiple_workers_work_load_2(self) -> None:
### the same as above but changing 'min' to 'exact', there's no solution
pb = ps.SchedulingProblem("MultipleWorkersWorkLoad2", horizon=12)
worker_1 = ps.Worker("Worker1")
worker_2 = ps.Worker("Worker2")
task1 = ps.FixedDurationTask("Task1", duration=10)
task1.add_required_resources([worker_1, worker_2])
ps.WorkLoad(worker_1, {(0, 4): 2})
ps.WorkLoad(worker_2, {(2, 6): 2}, kind="exact")
solver = ps.SchedulingSolver(pb)
solution = solver.solve()
self.assertFalse(solution)
def test_resource_work_load_exception(self) -> None:
ps.SchedulingProblem("ResourceWorkLoadException", horizon=12)
worker_1 = ps.Worker("Worker1")
with self.assertRaises(ValueError):
ps.WorkLoad(worker_1, {(0, 6): 2}, kind="foo")
def test_multiple_workers_work_load_1(self) -> None:
pb = ps.SchedulingProblem("MultipleWorkersWorkLoad1", horizon=12)
worker_1 = ps.Worker("Worker1")
worker_2 = ps.Worker("Worker2")
task1 = ps.FixedDurationTask("Task1", duration=10)
task1.add_required_resources([worker_1, worker_2])
ps.WorkLoad(worker_1, {(0, 4): 2})
ps.WorkLoad(worker_2, {(2, 6): 2}, kind="min")
solver = ps.SchedulingSolver(pb)
solution = solver.solve()
self.assertTrue(solution)
self.assertTrue(solution.tasks[task1.name].start == 2)
def test_resource_work_load_eq(self) -> None:
pb = ps.SchedulingProblem("ResourceWorkLoadEq", horizon=12)
task_1 = ps.FixedDurationTask("task1", duration=7)
worker_1 = ps.Worker("Worker1")
task_1.add_required_resource(worker_1)
ps.WorkLoad(worker_1, {(0, 6): 3}, kind="exact")
solver = ps.SchedulingSolver(pb)
solution = solver.solve()
self.assertTrue(solution)
# the only possible solution is that the task is scheduled form 3 to 9
self.assertEqual(solution.tasks[task_1.name].start, 3)
self.assertEqual(solution.tasks[task_1.name].end, 10)
def test_resource_work_load_basic(self) -> None:
pb = ps.SchedulingProblem("ResourceWorkLoadBasic", horizon=12)
task_1 = ps.FixedDurationTask("task1", duration=8)
worker_1 = ps.Worker("Worker1")
task_1.add_required_resource(worker_1)
ps.WorkLoad(worker_1, {(0, 6): 2})
solver = ps.SchedulingSolver(pb)
solution = solver.solve()
self.assertTrue(solution)
# the only possible solution is that the task is scheduled form 4 to 12
self.assertEqual(solution.tasks[task_1.name].start, 4)
self.assertEqual(solution.tasks[task_1.name].end, 12)
def test_resource_work_load_min(self) -> None:
pb = ps.SchedulingProblem("ResourceWorkLoadMin", horizon=20)
task_1 = ps.FixedDurationTask("task1", duration=7)
worker_1 = ps.Worker("Worker1")
task_1.add_required_resource(worker_1)
ps.WorkLoad(worker_1, {(6, 8): 2}, kind="min")
solver = ps.SchedulingSolver(pb)
solution = solver.solve()
self.assertTrue(solution)
# the only possible solution is that the task is scheduled form 3 to 9
self.assertTrue(solution.tasks[task_1.name].start <= 6)
self.assertTrue(solution.tasks[task_1.name].end >= 8)
def test_json_export_1(self):
pb = ps.SchedulingProblem("JSONExport1", horizon=10)
# tasks
task_1 = ps.FixedDurationTask("task1", duration=3)
task_2 = ps.VariableDurationTask("task2")
task_3 = ps.ZeroDurationTask("task3")
# buffers
buffer_1 = ps.NonConcurrentBuffer("Buffer1", initial_state=10)
buffer_2 = ps.NonConcurrentBuffer("Buffer2", initial_state=0)
# resources
worker_1 = ps.Worker("Worker1")
worker_2 = ps.Worker("Worker2")
worker_3 = ps.Worker("Worker3")
sw_1 = ps.SelectWorkers([worker_1, worker_2, worker_3])
sw_2 = ps.SelectWorkers([worker_1, worker_2, worker_3])
sw_3 = ps.SelectWorkers([worker_1, worker_2, worker_3])
ps.CumulativeWorker("CumulMachine1", size=3)
ps.CumulativeWorker("CumulMachine2", size=7)
# assign resources to tasks
task_1.add_required_resources([worker_1, worker_2])
task_2.add_required_resource(sw_1)
task_3.add_required_resource(sw_2)
# task constraints
ps.TaskPrecedence(task_1, task_2)
ps.TaskStartAt(task_1, 5)
ps.TaskUnloadBuffer(task_1, buffer_1, quantity=3)
ps.TaskLoadBuffer(task_1, buffer_2, quantity=2)
# resource constraints
ps.SameWorkers(sw_1, sw_2)
ps.DistinctWorkers(sw_2, sw_3)
ps.WorkLoad(worker_1, {(0, 6): 3, (19, 24): 4}, kind="exact")
ps.ResourceUnavailable(worker_1, [(1, 3), (6, 8)])
ps.ResourceTasksDistance(worker_1,
distance=4,
mode="exact",
list_of_time_intervals=[[10, 18]])
# export to json
solver = ps.SchedulingSolver(pb)
ps.export_json_to_file(pb, solver, "test_export_1.json")
def test_selectworker_work_load_1(self) -> None:
pb = ps.SchedulingProblem("SelectWorkerWorkLoad1", horizon=12)
worker_1 = ps.Worker("Worker1")
worker_2 = ps.Worker("Worker2")
task1 = ps.FixedDurationTask("Task1", duration=10)
task1.add_required_resource(ps.SelectWorkers([worker_1, worker_2], 1, "min"))
# the workload on worker_1 forces 0 between 4 and 8
# then the worker_1 can not be assigned
ps.WorkLoad(worker_1, {(4, 8): 0})
solver = ps.SchedulingSolver(pb)
solution = solver.solve()
print(solution)
self.assertTrue(solution)
self.assertTrue(
solution.tasks[task1.name].assigned_resources == [worker_2.name]
)
def test_resource_work_load_3(self) -> None:
# same problem, but we force two tasks to be scheduled at start and end
# of the planning
pb = ps.SchedulingProblem("ResourceWorkLoadUnavailability", horizon=12)
task_1 = ps.FixedDurationTask("task1", duration=4)
task_2 = ps.FixedDurationTask("task2", duration=4)
worker_1 = ps.Worker("Worker1")
task_1.add_required_resource(worker_1)
task_2.add_required_resource(worker_1)
c1 = ps.WorkLoad(worker_1, {(4, 8): 0})
pb.add_constraint(c1)
solver = ps.SchedulingSolver(pb)
solution = solver.solve()
self.assertTrue(solution)
# there should be one task from 0 to 4 and one task from 8 to 12.
self.assertTrue(solution.tasks[task_1.name].start == 0
or solution.tasks[task_2.name].start == 0)
self.assertTrue(solution.tasks[task_1.name].start == 8
or solution.tasks[task_2.name].start == 8)
# Create tasks and assign resources
tasks = []
for j in range(NB_TASKS_PER_WORKER):
tasks.append(
ps.FixedDurationTask(f"{name}__{j:02d}",
duration=1,
optional=True))
tasks[-1].add_required_resources([general_worker, worker])
workers.append({"name": name, "worker": worker, "tasks": tasks})
workload = {period: MAX_TASKS_PER_PERIOD for period in PERIODS}
workload[(0, horizon)] = MAX_TASKS_IN_PROBLEM
for worker in workers:
ps.WorkLoad(worker["worker"], workload, kind="max")
# Add constraints, define objective and solve problem
pb.add_objective_resource_utilization(general_worker)
solver = ps.SchedulingSolver(pb)
solution = solver.solve()
if not solution:
break
computation_times.append(time.perf_counter() - init_time)
plot_abs.append(i)
solver.print_statistics()
plt.title("Benchmark_mixed_constraints %s:%s" % (bench_date, bench_id))
plt.plot(plot_abs, computation_times, "D-", label="Computing time")
