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polish scheduling with transitions sat

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Laurent Perron
2018-09-17 11:29:30 +02:00
parent f48a402d6c
commit fea930f462
1 changed files with 13 additions and 12 deletions
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25
examples/python/scheduling_with_transitions_sat.py
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@@ -15,7 +15,7 @@ from ortools.sat.python import cp_model
def main():
"""Solves the scheduling with transitions problem."""
#------------------------------------------------------------------------------
#----------------------------------------------------------------------------
# Intermediate solution printer
class SolutionPrinter(cp_model.CpSolverSolutionCallback):
"""Print intermediate solutions."""
@@ -30,25 +30,25 @@ def main():
self.Value(makespan)))
self.__solution_count += 1
#------------------------------------------------------------------------------
#----------------------------------------------------------------------------
jobs = [[[(100, 0, 'R6'), (2, 1, 'R6')]], [[(2, 0, 'R3'), (100, 1, 'R3')]],
[[(100, 0, 'R1'), (16, 1, 'R1')]], [[(1, 0, 'R1'), (38, 1, 'R1')]],
[[(14, 0, 'R1'), (10, 1, 'R1')]], [[(16, 0, 'R3'), (17, 1, 'R3')]],
[[(14, 0, 'R3'), (14, 1, 'R3')]], [[(14, 0, 'R3'), (15, 1, 'R3')]],
[[(14, 0, 'R3'), (13, 1, 'R3')]], [[(100, 0, 'R1'), (38, 1, 'R1')]]]
#------------------------------------------------------------------------------
#----------------------------------------------------------------------------
# Helper data
num_jobs = len(jobs)
all_jobs = range(num_jobs)
num_machines = 2
all_machines = range(num_machines)
#------------------------------------------------------------------------------
#----------------------------------------------------------------------------
# Model
model = cp_model.CpModel()
#------------------------------------------------------------------------------
#----------------------------------------------------------------------------
# Sum each lot longest process time for max makespan
horizon = 0
for job in jobs:
@@ -60,7 +60,7 @@ def main():
print('Horizon = %i' % horizon)
#------------------------------------------------------------------------------
#----------------------------------------------------------------------------
# Scan the jobs and create the relevant variables and intervals.
intervals_per_machines = collections.defaultdict(list)
presences_per_machines = collections.defaultdict(list)
@@ -148,14 +148,14 @@ def main():
job_ends.append(previous_end)
#--------------------------------------------------------------------------------------------
#----------------------------------------------------------------------------
# Create machines constraints nonoverlap process
for machine_id in all_machines:
intervals = intervals_per_machines[machine_id]
if len(intervals) > 1:
model.AddNoOverlap(intervals)
#--------------------------------------------------------------------------------------------
#----------------------------------------------------------------------------
# Transition times and transition costs using a circuit constraints.
switch_literals = []
for machine_id in all_machines:
@@ -186,13 +186,14 @@ def main():
switch_literals.append(lit)
else:
transition_time = 0
# We add the reified transition to link the literals with the times of the tasks.
# We add the reified transition to link the literals with the times
# of the tasks.
model.Add(machine_starts[j] >= machine_ends[i] +
transition_time).OnlyEnforceIf(lit)
model.AddCircuit(arcs)
#--------------------------------------------------------------------------------------------
#----------------------------------------------------------------------------
# Objective
makespan = model.NewIntVar(0, horizon, 'makespan')
model.AddMaxEquality(makespan, job_ends)
@@ -201,14 +202,14 @@ def main():
model.Minimize(makespan * makespan_weight +
sum(switch_literals) * transition_weight)
#--------------------------------------------------------------------------------------------
#----------------------------------------------------------------------------
# Solve
solver = cp_model.CpSolver()
solver.parameters.max_time_in_seconds = 60 * 60 * 2
solution_printer = SolutionPrinter()
status = solver.SolveWithSolutionCallback(model, solution_printer)
#--------------------------------------------------------------------------------------------
#----------------------------------------------------------------------------
# Print solution
if status == cp_model.FEASIBLE or status == cp_model.OPTIMAL:
for job_id in all_jobs: