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polish minimal jobshop python sat sample

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Laurent Perron
2018-11-08 13:31:27 +01:00
parent 1665e776dc
commit 5d28e9fbcb
2 changed files with 28 additions and 327 deletions
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299
examples/python/code_samples_sat.py
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@@ -21,281 +21,6 @@ import collections
from ortools.sat.python import cp_model
def CodeSample():
model = cp_model.CpModel()
x = model.NewBoolVar('x')
print(x)
def LiteralSample():
model = cp_model.CpModel()
x = model.NewBoolVar('x')
not_x = x.Not()
print(x)
print(not_x)
def BoolOrSample():
model = cp_model.CpModel()
x = model.NewBoolVar('x')
y = model.NewBoolVar('y')
model.AddBoolOr([x, y.Not()])
def ReifiedSample():
"""Showcase creating a reified constraint."""
model = cp_model.CpModel()
x = model.NewBoolVar('x')
y = model.NewBoolVar('y')
b = model.NewBoolVar('b')
# First version using a half-reified bool and.
model.AddBoolAnd([x, y.Not()]).OnlyEnforceIf(b)
# Second version using implications.
model.AddImplication(b, x)
model.AddImplication(b, y.Not())
# Third version using bool or.
model.AddBoolOr([b.Not(), x])
model.AddBoolOr([b.Not(), y.Not()])
def RabbitsAndPheasants():
"""Solves the rabbits + pheasants problem."""
model = cp_model.CpModel()
r = model.NewIntVar(0, 100, 'r')
p = model.NewIntVar(0, 100, 'p')
# 20 heads.
model.Add(r + p == 20)
# 56 legs.
model.Add(4 * r + 2 * p == 56)
# Solves and prints out the solution.
solver = cp_model.CpSolver()
status = solver.Solve(model)
if status == cp_model.FEASIBLE:
print('%i rabbits and %i pheasants' % (solver.Value(r), solver.Value(p)))
def BinpackingProblem():
"""Solves a bin-packing problem."""
# Data.
bin_capacity = 100
slack_capacity = 20
num_bins = 10
all_bins = range(num_bins)
items = [(20, 12), (15, 12), (30, 8), (45, 5)]
num_items = len(items)
all_items = range(num_items)
# Model.
model = cp_model.CpModel()
# Main variables.
x = {}
for i in all_items:
num_copies = items[i][1]
for b in all_bins:
x[(i, b)] = model.NewIntVar(0, num_copies, 'x_%i_%i' % (i, b))
# Load variables.
load = [model.NewIntVar(0, bin_capacity, 'load_%i' % b) for b in all_bins]
# Slack variables.
slacks = [model.NewBoolVar('slack_%i' % b) for b in all_bins]
# Links load and x.
for b in all_bins:
model.Add(load[b] == sum(x[(i, b)] * items[i][0] for i in all_items))
# Place all items.
for i in all_items:
model.Add(sum(x[(i, b)] for b in all_bins) == items[i][1])
# Links load and slack through an equivalence relation.
safe_capacity = bin_capacity - slack_capacity
for b in all_bins:
# slack[b] => load[b] <= safe_capacity.
model.Add(load[b] <= safe_capacity).OnlyEnforceIf(slacks[b])
# not(slack[b]) => load[b] > safe_capacity.
model.Add(load[b] > safe_capacity).OnlyEnforceIf(slacks[b].Not())
# Maximize sum of slacks.
model.Maximize(sum(slacks))
# Solves and prints out the solution.
solver = cp_model.CpSolver()
status = solver.Solve(model)
print('Solve status: %s' % solver.StatusName(status))
if status == cp_model.OPTIMAL:
print('Optimal objective value: %i' % solver.ObjectiveValue())
print('Statistics')
print(' - conflicts : %i' % solver.NumConflicts())
print(' - branches : %i' % solver.NumBranches())
print(' - wall time : %f s' % solver.WallTime())
def IntervalSample():
model = cp_model.CpModel()
horizon = 100
start_var = model.NewIntVar(0, horizon, 'start')
duration = 10 # Python cp/sat code accept integer variables or constants.
end_var = model.NewIntVar(0, horizon, 'end')
interval_var = model.NewIntervalVar(start_var, duration, end_var, 'interval')
print('start = %s, duration = %i, end = %s, interval = %s' %
(start_var, duration, end_var, interval_var))
def OptionalIntervalSample():
model = cp_model.CpModel()
horizon = 100
start_var = model.NewIntVar(0, horizon, 'start')
duration = 10 # Python cp/sat code accept integer variables or constants.
end_var = model.NewIntVar(0, horizon, 'end')
presence_var = model.NewBoolVar('presence')
interval_var = model.NewOptionalIntervalVar(start_var, duration, end_var,
presence_var, 'interval')
print('start = %s, duration = %i, end = %s, presence = %s, interval = %s' %
(start_var, duration, end_var, presence_var, interval_var))
def MinimalCpSat():
"""Minimal CP-SAT example to showcase calling the solver."""
# Creates the model.
model = cp_model.CpModel()
# Creates the variables.
num_vals = 3
x = model.NewIntVar(0, num_vals - 1, 'x')
y = model.NewIntVar(0, num_vals - 1, 'y')
z = model.NewIntVar(0, num_vals - 1, 'z')
# Creates the constraints.
model.Add(x != y)
# Creates a solver and solves the model.
solver = cp_model.CpSolver()
status = solver.Solve(model)
if status == cp_model.FEASIBLE:
print('x = %i' % solver.Value(x))
print('y = %i' % solver.Value(y))
print('z = %i' % solver.Value(z))
def MinimalCpSatWithTimeLimit():
"""Minimal CP-SAT example to showcase calling the solver."""
# Creates the model.
model = cp_model.CpModel()
# Creates the variables.
num_vals = 3
x = model.NewIntVar(0, num_vals - 1, 'x')
y = model.NewIntVar(0, num_vals - 1, 'y')
z = model.NewIntVar(0, num_vals - 1, 'z')
# Adds an all-different constraint.
model.Add(x != y)
# Creates a solver and solves the model.
solver = cp_model.CpSolver()
# Sets a time limit of 10 seconds.
solver.parameters.max_time_in_seconds = 10.0
status = solver.Solve(model)
if status == cp_model.FEASIBLE:
print('x = %i' % solver.Value(x))
print('y = %i' % solver.Value(y))
print('z = %i' % solver.Value(z))
# You need to subclass the cp_model.CpSolverSolutionCallback class.
class VarArrayAndObjectiveSolutionPrinter(cp_model.CpSolverSolutionCallback):
"""Print intermediate solutions."""
def __init__(self, variables):
cp_model.CpSolverSolutionCallback.__init__(self)
self.__variables = variables
self.__solution_count = 0
def OnSolutionCallback(self):
print('Solution %i' % self.__solution_count)
print(' objective value = %i' % self.ObjectiveValue())
for v in self.__variables:
print(' %s = %i' % (v, self.Value(v)), end=' ')
print()
self.__solution_count += 1
def SolutionCount(self):
return self.__solution_count
def MinimalCpSatPrintIntermediateSolutions():
"""Showcases printing intermediate solutions found during search."""
# Creates the model.
model = cp_model.CpModel()
# Creates the variables.
num_vals = 3
x = model.NewIntVar(0, num_vals - 1, 'x')
y = model.NewIntVar(0, num_vals - 1, 'y')
z = model.NewIntVar(0, num_vals - 1, 'z')
# Creates the constraints.
model.Add(x != y)
model.Maximize(x + 2 * y + 3 * z)
# Creates a solver and solves.
solver = cp_model.CpSolver()
solution_printer = VarArrayAndObjectiveSolutionPrinter([x, y, z])
status = solver.SolveWithSolutionCallback(model, solution_printer)
print('Status = %s' % solver.StatusName(status))
print('Number of solutions found: %i' % solution_printer.SolutionCount())
class VarArraySolutionPrinter(cp_model.CpSolverSolutionCallback):
"""Print intermediate solutions."""
def __init__(self, variables):
cp_model.CpSolverSolutionCallback.__init__(self)
self.__variables = variables
self.__solution_count = 0
def OnSolutionCallback(self):
self.__solution_count += 1
for v in self.__variables:
print('%s=%i' % (v, self.Value(v)), end=' ')
print()
def SolutionCount(self):
return self.__solution_count
def MinimalCpSatAllSolutions():
"""Showcases calling the solver to search for all solutions."""
# Creates the model.
model = cp_model.CpModel()
# Creates the variables.
num_vals = 3
x = model.NewIntVar(0, num_vals - 1, 'x')
y = model.NewIntVar(0, num_vals - 1, 'y')
z = model.NewIntVar(0, num_vals - 1, 'z')
# Create the constraints.
model.Add(x != y)
# Create a solver and solve.
solver = cp_model.CpSolver()
solution_printer = VarArraySolutionPrinter([x, y, z])
status = solver.SearchForAllSolutions(model, solution_printer)
print('Status = %s' % solver.StatusName(status))
print('Number of solutions found: %i' % solution_printer.SolutionCount())
def SolvingLinearProblem():
"""CP-SAT linear solver problem."""
# Create a model.
@@ -428,30 +153,6 @@ def MinimalJobShop():
def main(_):
print('--- CodeSample ---')
CodeSample()
print('--- LiteralSample ---')
LiteralSample()
print('--- BoolOrSample ---')
BoolOrSample()
print('--- ReifiedSample ---')
ReifiedSample()
print('--- RabbitsAndPheasants ---')
RabbitsAndPheasants()
print('--- BinpackingProblem ---')
BinpackingProblem()
print('--- IntervalSample ---')
IntervalSample()
print('--- OptionalIntervalSample ---')
OptionalIntervalSample()
print('--- MinimalCpSat ---')
MinimalCpSat()
print('--- MinimalCpSatWithTimeLimit ---')
MinimalCpSatWithTimeLimit()
print('--- MinimalCpSatPrintIntermediateSolutions ---')
MinimalCpSatPrintIntermediateSolutions()
print('--- MinimalCpSatAllSolutions ---')
MinimalCpSatAllSolutions()
print('--- SolvingLinearProblem ---')
SolvingLinearProblem()
print('--- MinimalJobShop ---')