4f381f6d07
* bump abseil to 20250814 * bump protobuf to v32.0 * cmake: add ccache auto support * backport flatzinc, math_opt and sat update
99 lines
3.3 KiB
Python
99 lines
3.3 KiB
Python
#!/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]
|
|
"""Code sample to demonstrates how to detect if two intervals overlap."""
|
|
|
|
from ortools.sat.python import cp_model
|
|
|
|
|
|
class VarArraySolutionPrinter(cp_model.CpSolverSolutionCallback):
|
|
"""Print intermediate solutions."""
|
|
|
|
def __init__(self, variables: list[cp_model.IntVar]):
|
|
cp_model.CpSolverSolutionCallback.__init__(self)
|
|
self.__variables = variables
|
|
|
|
def on_solution_callback(self) -> None:
|
|
for v in self.__variables:
|
|
print(f"{v}={self.value(v)}", end=" ")
|
|
print()
|
|
|
|
|
|
def overlapping_interval_sample_sat():
|
|
"""Create the overlapping Boolean variables and enumerate all states."""
|
|
model = cp_model.CpModel()
|
|
|
|
horizon = 7
|
|
|
|
# First interval.
|
|
start_var_a = model.new_int_var(0, horizon, "start_a")
|
|
duration_a = 3
|
|
end_var_a = model.new_int_var(0, horizon, "end_a")
|
|
unused_interval_var_a = model.new_interval_var(
|
|
start_var_a, duration_a, end_var_a, "interval_a"
|
|
)
|
|
|
|
# Second interval.
|
|
start_var_b = model.new_int_var(0, horizon, "start_b")
|
|
duration_b = 2
|
|
end_var_b = model.new_int_var(0, horizon, "end_b")
|
|
unused_interval_var_b = model.new_interval_var(
|
|
start_var_b, duration_b, end_var_b, "interval_b"
|
|
)
|
|
|
|
# a_after_b Boolean variable.
|
|
a_after_b = model.new_bool_var("a_after_b")
|
|
model.add(start_var_a >= end_var_b).only_enforce_if(a_after_b)
|
|
model.add(start_var_a < end_var_b).only_enforce_if(~a_after_b)
|
|
|
|
# b_after_a Boolean variable.
|
|
b_after_a = model.new_bool_var("b_after_a")
|
|
model.add(start_var_b >= end_var_a).only_enforce_if(b_after_a)
|
|
model.add(start_var_b < end_var_a).only_enforce_if(~b_after_a)
|
|
|
|
# Result Boolean variable.
|
|
a_overlaps_b = model.new_bool_var("a_overlaps_b")
|
|
|
|
# Option a: using only clauses
|
|
model.add_bool_or(a_after_b, b_after_a, a_overlaps_b)
|
|
model.add_implication(a_after_b, ~a_overlaps_b)
|
|
model.add_implication(b_after_a, ~a_overlaps_b)
|
|
|
|
# Option b: using an exactly one constraint.
|
|
# model.add_exactly_one(a_after_b, b_after_a, a_overlaps_b)
|
|
|
|
# Search for start values in increasing order for the two intervals.
|
|
model.add_decision_strategy(
|
|
[start_var_a, start_var_b],
|
|
cp_model.CHOOSE_FIRST,
|
|
cp_model.SELECT_MIN_VALUE,
|
|
)
|
|
|
|
# Create a solver and solve with a fixed search.
|
|
solver = cp_model.CpSolver()
|
|
|
|
# Force the solver to follow the decision strategy exactly.
|
|
solver.parameters.search_branching = cp_model.FIXED_SEARCH
|
|
# Enumerate all solutions.
|
|
solver.parameters.enumerate_all_solutions = True
|
|
|
|
# Search and print out all solutions.
|
|
solution_printer = VarArraySolutionPrinter([start_var_a, start_var_b, a_overlaps_b])
|
|
solver.solve(model, solution_printer)
|
|
|
|
|
|
overlapping_interval_sample_sat()
|
|
# [END program]
|