1000 lines
39 KiB
C++
1000 lines
39 KiB
C++
// Copyright 2010-2024 Google LLC
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "ortools/sat/diffn.h"
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#include <stddef.h>
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#include <algorithm>
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#include <cstddef>
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#include <cstdint>
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#include <iterator>
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#include <limits>
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#include <optional>
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#include <string>
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#include <utility>
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#include <vector>
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#include "absl/container/flat_hash_set.h"
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#include "absl/container/inlined_vector.h"
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#include "absl/log/check.h"
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#include "absl/types/span.h"
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#include "ortools/base/logging.h"
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#include "ortools/sat/2d_orthogonal_packing.h"
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#include "ortools/sat/cumulative_energy.h"
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#include "ortools/sat/diffn_util.h"
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#include "ortools/sat/disjunctive.h"
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#include "ortools/sat/integer.h"
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#include "ortools/sat/integer_expr.h"
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#include "ortools/sat/intervals.h"
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#include "ortools/sat/linear_constraint.h"
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#include "ortools/sat/model.h"
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#include "ortools/sat/sat_base.h"
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#include "ortools/sat/sat_parameters.pb.h"
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#include "ortools/sat/timetable.h"
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#include "ortools/util/saturated_arithmetic.h"
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#include "ortools/util/strong_integers.h"
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namespace operations_research {
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namespace sat {
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namespace {
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IntegerVariable CreateVariableWithTightDomain(
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absl::Span<const AffineExpression> exprs, Model* model) {
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IntegerValue min = kMaxIntegerValue;
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IntegerValue max = kMinIntegerValue;
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auto* integer_trail = model->GetOrCreate<IntegerTrail>();
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for (const AffineExpression& e : exprs) {
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min = std::min(min, integer_trail->LevelZeroLowerBound(e));
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max = std::max(max, integer_trail->LevelZeroUpperBound(e));
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}
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return integer_trail->AddIntegerVariable(min, max);
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}
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// TODO(user): Use the faster variable only version if all expressions reduce
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// to a single variable?
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IntegerVariable CreateVariableEqualToMinOf(
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absl::Span<const AffineExpression> exprs, Model* model) {
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std::vector<LinearExpression> converted;
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for (const AffineExpression& affine : exprs) {
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LinearExpression e;
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e.offset = affine.constant;
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if (affine.var != kNoIntegerVariable) {
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e.vars.push_back(affine.var);
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e.coeffs.push_back(affine.coeff);
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}
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converted.push_back(e);
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}
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LinearExpression target;
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const IntegerVariable var = CreateVariableWithTightDomain(exprs, model);
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target.vars.push_back(var);
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target.coeffs.push_back(IntegerValue(1));
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model->Add(IsEqualToMinOf(target, converted));
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return var;
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}
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IntegerVariable CreateVariableEqualToMaxOf(
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absl::Span<const AffineExpression> exprs, Model* model) {
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std::vector<LinearExpression> converted;
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for (const AffineExpression& affine : exprs) {
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LinearExpression e;
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e.offset = affine.constant;
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if (affine.var != kNoIntegerVariable) {
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e.vars.push_back(affine.var);
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e.coeffs.push_back(affine.coeff);
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}
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converted.push_back(NegationOf(e));
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}
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LinearExpression target;
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const IntegerVariable var = CreateVariableWithTightDomain(exprs, model);
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target.vars.push_back(NegationOf(var));
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target.coeffs.push_back(IntegerValue(1));
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model->Add(IsEqualToMinOf(target, converted));
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return var;
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}
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// Add a cumulative relaxation. That is, on one dimension, it does not enforce
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// the rectangle aspect, allowing vertical slices to move freely.
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void AddDiffnCumulativeRelationOnX(SchedulingConstraintHelper* x,
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SchedulingConstraintHelper* y,
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Model* model) {
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// TODO(user): Use conditional affine min/max !!
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const IntegerVariable min_start_var =
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CreateVariableEqualToMinOf(y->Starts(), model);
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const IntegerVariable max_end_var =
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CreateVariableEqualToMaxOf(y->Ends(), model);
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// (max_end - min_start) >= capacity.
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auto* integer_trail = model->GetOrCreate<IntegerTrail>();
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const AffineExpression capacity(model->Add(NewIntegerVariable(
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0, CapSub(integer_trail->UpperBound(max_end_var).value(),
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integer_trail->LowerBound(min_start_var).value()))));
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const std::vector<int64_t> coeffs = {-capacity.coeff.value(), -1, 1};
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model->Add(
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WeightedSumGreaterOrEqual({capacity.var, min_start_var, max_end_var},
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coeffs, capacity.constant.value()));
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SchedulingDemandHelper* demands =
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model->GetOrCreate<IntervalsRepository>()->GetOrCreateDemandHelper(
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x, y->Sizes());
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// Propagator responsible for applying Timetabling filtering rule. It
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// increases the minimum of the start variables, decrease the maximum of the
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// end variables, and increase the minimum of the capacity variable.
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const SatParameters& params = *model->GetOrCreate<SatParameters>();
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if (params.use_timetabling_in_no_overlap_2d()) {
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TimeTablingPerTask* time_tabling =
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new TimeTablingPerTask(capacity, x, demands, model);
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time_tabling->RegisterWith(model->GetOrCreate<GenericLiteralWatcher>());
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model->TakeOwnership(time_tabling);
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}
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// Propagator responsible for applying the Overload Checking filtering rule.
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// It increases the minimum of the capacity variable.
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if (params.use_energetic_reasoning_in_no_overlap_2d()) {
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AddCumulativeOverloadChecker(capacity, x, demands, model);
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}
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}
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// This function will fill the helper why the two boxes always overlap on that
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// dimension.
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void ClearAndAddMandatoryOverlapReason(int box1, int box2,
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SchedulingConstraintHelper* helper) {
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helper->ClearReason();
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helper->AddPresenceReason(box1);
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helper->AddPresenceReason(box2);
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helper->AddReasonForBeingBefore(box1, box2);
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helper->AddReasonForBeingBefore(box2, box1);
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}
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bool ClearAndAddTwoBoxesConflictReason(int box1, int box2,
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SchedulingConstraintHelper* x,
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SchedulingConstraintHelper* y) {
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ClearAndAddMandatoryOverlapReason(box1, box2, x);
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ClearAndAddMandatoryOverlapReason(box1, box2, y);
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x->ImportOtherReasons(*y);
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return x->ReportConflict();
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}
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} // namespace
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void AddNonOverlappingRectangles(const std::vector<IntervalVariable>& x,
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const std::vector<IntervalVariable>& y,
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Model* model) {
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IntervalsRepository* repository = model->GetOrCreate<IntervalsRepository>();
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SchedulingConstraintHelper* x_helper = repository->GetOrCreateHelper(x);
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SchedulingConstraintHelper* y_helper = repository->GetOrCreateHelper(y);
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NonOverlappingRectanglesDisjunctivePropagator* constraint =
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new NonOverlappingRectanglesDisjunctivePropagator(x_helper, y_helper,
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model);
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constraint->Register(/*fast_priority=*/3, /*slow_priority=*/4);
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model->TakeOwnership(constraint);
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RectanglePairwisePropagator* pairwise_propagator =
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new RectanglePairwisePropagator(x_helper, y_helper, model);
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GenericLiteralWatcher* const watcher =
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model->GetOrCreate<GenericLiteralWatcher>();
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watcher->SetPropagatorPriority(pairwise_propagator->RegisterWith(watcher), 4);
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model->TakeOwnership(pairwise_propagator);
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const SatParameters& params = *model->GetOrCreate<SatParameters>();
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const bool add_cumulative_relaxation =
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params.use_timetabling_in_no_overlap_2d() ||
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params.use_energetic_reasoning_in_no_overlap_2d();
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if (add_cumulative_relaxation) {
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// We must first check if the cumulative relaxation is possible.
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bool some_boxes_are_only_optional_on_x = false;
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bool some_boxes_are_only_optional_on_y = false;
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for (int i = 0; i < x.size(); ++i) {
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if (x_helper->IsOptional(i) && y_helper->IsOptional(i) &&
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x_helper->PresenceLiteral(i) != y_helper->PresenceLiteral(i)) {
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// Abort as the task would be conditioned by two literals.
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return;
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}
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if (x_helper->IsOptional(i) && !y_helper->IsOptional(i)) {
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// We cannot use x_size as the demand of the cumulative based on
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// the y_intervals.
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some_boxes_are_only_optional_on_x = true;
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}
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if (y_helper->IsOptional(i) && !x_helper->IsOptional(i)) {
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// We cannot use y_size as the demand of the cumulative based on
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// the y_intervals.
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some_boxes_are_only_optional_on_y = true;
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}
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}
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if (!some_boxes_are_only_optional_on_y) {
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AddDiffnCumulativeRelationOnX(x_helper, y_helper, model);
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}
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if (!some_boxes_are_only_optional_on_x) {
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AddDiffnCumulativeRelationOnX(y_helper, x_helper, model);
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}
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}
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if (params.use_area_energetic_reasoning_in_no_overlap_2d()) {
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NonOverlappingRectanglesEnergyPropagator* energy_constraint =
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new NonOverlappingRectanglesEnergyPropagator(x_helper, y_helper, model);
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GenericLiteralWatcher* const watcher =
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model->GetOrCreate<GenericLiteralWatcher>();
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watcher->SetPropagatorPriority(energy_constraint->RegisterWith(watcher), 5);
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model->TakeOwnership(energy_constraint);
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}
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}
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#define RETURN_IF_FALSE(f) \
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if (!(f)) return false;
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NonOverlappingRectanglesEnergyPropagator::
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~NonOverlappingRectanglesEnergyPropagator() {
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if (!VLOG_IS_ON(1)) return;
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std::vector<std::pair<std::string, int64_t>> stats;
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stats.push_back(
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{"NonOverlappingRectanglesEnergyPropagator/called", num_calls_});
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stats.push_back(
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{"NonOverlappingRectanglesEnergyPropagator/conflicts", num_conflicts_});
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stats.push_back(
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{"NonOverlappingRectanglesEnergyPropagator/conflicts_two_boxes",
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num_conflicts_two_boxes_});
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stats.push_back({"NonOverlappingRectanglesEnergyPropagator/refined",
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num_refined_conflicts_});
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stats.push_back(
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{"NonOverlappingRectanglesEnergyPropagator/conflicts_with_slack",
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num_conflicts_with_slack_});
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shared_stats_->AddStats(stats);
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}
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bool NonOverlappingRectanglesEnergyPropagator::Propagate() {
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// TODO(user): double-check/revisit the algo for box of variable sizes.
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const int num_boxes = x_.NumTasks();
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if (!x_.SynchronizeAndSetTimeDirection(true)) return false;
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if (!y_.SynchronizeAndSetTimeDirection(true)) return false;
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Rectangle bounding_box = {.x_min = std::numeric_limits<IntegerValue>::max(),
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.x_max = std::numeric_limits<IntegerValue>::min(),
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.y_min = std::numeric_limits<IntegerValue>::max(),
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.y_max = std::numeric_limits<IntegerValue>::min()};
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std::vector<RectangleInRange> active_box_ranges;
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active_box_ranges.reserve(num_boxes);
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for (int box = 0; box < num_boxes; ++box) {
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if (x_.SizeMin(box) == 0 || y_.SizeMin(box) == 0) continue;
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if (!x_.IsPresent(box) || !y_.IsPresent(box)) continue;
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bounding_box.x_min = std::min(bounding_box.x_min, x_.StartMin(box));
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bounding_box.x_max = std::max(bounding_box.x_max, x_.EndMax(box));
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bounding_box.y_min = std::min(bounding_box.y_min, y_.StartMin(box));
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bounding_box.y_max = std::max(bounding_box.y_max, y_.EndMax(box));
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active_box_ranges.push_back(RectangleInRange{
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.box_index = box,
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.bounding_area = {.x_min = x_.StartMin(box),
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.x_max = x_.StartMax(box) + x_.SizeMin(box),
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.y_min = y_.StartMin(box),
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.y_max = y_.StartMax(box) + y_.SizeMin(box)},
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.x_size = x_.SizeMin(box),
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.y_size = y_.SizeMin(box)});
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}
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if (active_box_ranges.size() < 2) {
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return true;
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}
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// Our algo is quadratic, so we don't want to run it on really large problems.
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if (active_box_ranges.size() > 1000) {
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return true;
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}
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if (std::max(bounding_box.SizeX(), bounding_box.SizeY()) *
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active_box_ranges.size() >
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std::numeric_limits<int32_t>::max()) {
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// Avoid integer overflows if the area of the boxes get comparable with
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// INT64_MAX
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return true;
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}
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num_calls_++;
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std::optional<Conflict> best_conflict =
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FindConflict(std::move(active_box_ranges));
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if (!best_conflict.has_value()) {
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return true;
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}
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num_conflicts_++;
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// We found a conflict, so we can afford to run the propagator again to
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// search for a best explanation. This is specially the case since we only
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// want to re-run it over the items that participate in the conflict, so it is
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// a much smaller problem.
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IntegerValue best_explanation_size =
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best_conflict->opp_result.GetItemsParticipatingOnConflict().size();
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bool refined = false;
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while (true) {
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std::vector<RectangleInRange> items_participating_in_conflict;
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items_participating_in_conflict.reserve(
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best_conflict->items_for_opp.size());
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for (const auto& item :
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best_conflict->opp_result.GetItemsParticipatingOnConflict()) {
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items_participating_in_conflict.push_back(
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best_conflict->items_for_opp[item.index]);
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}
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std::optional<Conflict> conflict =
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FindConflict(items_participating_in_conflict);
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if (!conflict.has_value()) break;
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// We prefer an explanation with the least number of boxes.
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if (conflict->opp_result.GetItemsParticipatingOnConflict().size() >=
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best_explanation_size) {
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// The new explanation isn't better than the old one. Stop trying.
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break;
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}
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best_explanation_size =
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conflict->opp_result.GetItemsParticipatingOnConflict().size();
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best_conflict = std::move(conflict);
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refined = true;
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}
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num_refined_conflicts_ += refined;
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const std::vector<RectangleInRange> generalized_explanation =
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GeneralizeExplanation(*best_conflict);
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if (best_explanation_size == 2) {
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num_conflicts_two_boxes_++;
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}
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BuildAndReportEnergyTooLarge(generalized_explanation);
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return false;
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}
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std::optional<NonOverlappingRectanglesEnergyPropagator::Conflict>
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NonOverlappingRectanglesEnergyPropagator::FindConflict(
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std::vector<RectangleInRange> active_box_ranges) {
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const auto rectangles_with_too_much_energy =
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FindRectanglesWithEnergyConflictMC(active_box_ranges, *random_, 1.0, 0.8);
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if (rectangles_with_too_much_energy.conflicts.empty() &&
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rectangles_with_too_much_energy.candidates.empty()) {
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return std::nullopt;
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}
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Conflict best_conflict;
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// Sample 10 rectangles (at least five among the ones for which we already
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// detected an energy overflow), extract an orthogonal packing subproblem for
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// each and look for conflict. Sampling avoids making this heuristic too
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// costly.
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constexpr int kSampleSize = 10;
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absl::InlinedVector<Rectangle, kSampleSize> sampled_rectangles;
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std::sample(rectangles_with_too_much_energy.conflicts.begin(),
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rectangles_with_too_much_energy.conflicts.end(),
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std::back_inserter(sampled_rectangles), 5, *random_);
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std::sample(rectangles_with_too_much_energy.candidates.begin(),
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rectangles_with_too_much_energy.candidates.end(),
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std::back_inserter(sampled_rectangles),
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kSampleSize - sampled_rectangles.size(), *random_);
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std::sort(sampled_rectangles.begin(), sampled_rectangles.end(),
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[](const Rectangle& a, const Rectangle& b) {
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const bool larger = std::make_pair(a.SizeX(), a.SizeY()) >
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std::make_pair(b.SizeX(), b.SizeY());
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// Double-check the invariant from
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// FindRectanglesWithEnergyConflictMC() that given two returned
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// rectangles there is one that is fully inside the other.
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if (larger) {
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// Rectangle b is fully contained inside a
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DCHECK(a.x_min <= b.x_min && a.x_max >= b.x_max &&
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a.y_min <= b.y_min && a.y_max >= b.y_max);
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} else {
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// Rectangle a is fully contained inside b
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DCHECK(a.x_min >= b.x_min && a.x_max <= b.x_max &&
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a.y_min >= b.y_min && a.y_max <= b.y_max);
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}
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return larger;
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});
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std::vector<IntegerValue> sizes_x, sizes_y;
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sizes_x.reserve(active_box_ranges.size());
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sizes_y.reserve(active_box_ranges.size());
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std::vector<RectangleInRange> filtered_items;
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filtered_items.reserve(active_box_ranges.size());
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for (const Rectangle& r : sampled_rectangles) {
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sizes_x.clear();
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sizes_y.clear();
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filtered_items.clear();
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for (int i = 0; i < active_box_ranges.size(); ++i) {
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const RectangleInRange& box = active_box_ranges[i];
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const Rectangle intersection = box.GetMinimumIntersection(r);
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if (intersection.SizeX() > 0 && intersection.SizeY() > 0) {
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sizes_x.push_back(intersection.SizeX());
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sizes_y.push_back(intersection.SizeY());
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filtered_items.push_back(box);
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}
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}
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// This check the feasibility of a related orthogonal packing problem where
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// our rectangle is the bounding box, and we need to fit inside it a set of
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// items corresponding to the minimum intersection of the original items
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// with this bounding box.
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const auto opp_result = orthogonal_packing_checker_.TestFeasibility(
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sizes_x, sizes_y, {r.SizeX(), r.SizeY()},
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OrthogonalPackingOptions{
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.use_pairwise = true,
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.use_dff_f0 = true,
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.use_dff_f2 = true,
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.brute_force_threshold = 6,
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.dff2_max_number_of_parameters_to_check = 100});
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if (opp_result.GetResult() == OrthogonalPackingResult::Status::INFEASIBLE &&
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(best_conflict.opp_result.GetResult() !=
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OrthogonalPackingResult::Status::INFEASIBLE ||
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best_conflict.opp_result.GetItemsParticipatingOnConflict().size() >
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opp_result.GetItemsParticipatingOnConflict().size())) {
|
|
best_conflict.items_for_opp = filtered_items;
|
|
best_conflict.opp_result = opp_result;
|
|
best_conflict.rectangle_with_too_much_energy = r;
|
|
}
|
|
// Use the fact that our rectangles are ordered in shrinking order to remove
|
|
// all items that will never contribute again.
|
|
filtered_items.swap(active_box_ranges);
|
|
}
|
|
if (best_conflict.opp_result.GetResult() ==
|
|
OrthogonalPackingResult::Status::INFEASIBLE) {
|
|
return best_conflict;
|
|
} else {
|
|
return std::nullopt;
|
|
}
|
|
}
|
|
|
|
std::vector<RectangleInRange>
|
|
NonOverlappingRectanglesEnergyPropagator::GeneralizeExplanation(
|
|
const Conflict& conflict) {
|
|
const Rectangle& rectangle = conflict.rectangle_with_too_much_energy;
|
|
OrthogonalPackingResult relaxed_result = conflict.opp_result;
|
|
|
|
// Use the potential slack to have a stronger reason.
|
|
int used_slack_count = 0;
|
|
const auto& items = relaxed_result.GetItemsParticipatingOnConflict();
|
|
for (int i = 0; i < items.size(); ++i) {
|
|
if (!relaxed_result.HasSlack()) {
|
|
break;
|
|
}
|
|
const RectangleInRange& range = conflict.items_for_opp[items[i].index];
|
|
const RectangleInRange item_in_zero_level_range = {
|
|
.bounding_area = {.x_min = x_.LevelZeroStartMin(range.box_index),
|
|
.x_max = x_.LevelZeroStartMax(range.box_index) +
|
|
range.x_size,
|
|
.y_min = y_.LevelZeroStartMin(range.box_index),
|
|
.y_max = y_.LevelZeroStartMax(range.box_index) +
|
|
range.y_size},
|
|
.x_size = range.x_size,
|
|
.y_size = range.y_size};
|
|
// There is no point trying to intersect less the item with the rectangle
|
|
// than it would on zero-level. So do not waste the slack with it.
|
|
const Rectangle max_overlap =
|
|
item_in_zero_level_range.GetMinimumIntersection(rectangle);
|
|
used_slack_count += relaxed_result.TryUseSlackToReduceItemSize(
|
|
i, OrthogonalPackingResult::Coord::kCoordX, max_overlap.SizeX());
|
|
used_slack_count += relaxed_result.TryUseSlackToReduceItemSize(
|
|
i, OrthogonalPackingResult::Coord::kCoordY, max_overlap.SizeY());
|
|
}
|
|
num_conflicts_with_slack_ += (used_slack_count > 0);
|
|
VLOG_EVERY_N_SEC(2, 3)
|
|
<< "Found a conflict on the OPP sub-problem of rectangle: " << rectangle
|
|
<< " using "
|
|
<< conflict.opp_result.GetItemsParticipatingOnConflict().size() << "/"
|
|
<< conflict.items_for_opp.size() << " items.";
|
|
|
|
std::vector<RectangleInRange> ranges_for_explanation;
|
|
ranges_for_explanation.reserve(conflict.items_for_opp.size());
|
|
std::vector<OrthogonalPackingResult::Item> sorted_items =
|
|
relaxed_result.GetItemsParticipatingOnConflict();
|
|
// TODO(user) understand why sorting high-impact items first improves the
|
|
// benchmarks
|
|
std::sort(sorted_items.begin(), sorted_items.end(),
|
|
[](const OrthogonalPackingResult::Item& a,
|
|
const OrthogonalPackingResult::Item& b) {
|
|
return a.size_x * a.size_y > b.size_x * b.size_y;
|
|
});
|
|
for (const auto& item : sorted_items) {
|
|
const RectangleInRange& range = conflict.items_for_opp[item.index];
|
|
ranges_for_explanation.push_back(
|
|
RectangleInRange::BiggestWithMinIntersection(rectangle, range,
|
|
item.size_x, item.size_y));
|
|
}
|
|
return ranges_for_explanation;
|
|
}
|
|
|
|
int NonOverlappingRectanglesEnergyPropagator::RegisterWith(
|
|
GenericLiteralWatcher* watcher) {
|
|
const int id = watcher->Register(this);
|
|
x_.WatchAllTasks(id, watcher, /*watch_start_max=*/true,
|
|
/*watch_end_max=*/true);
|
|
y_.WatchAllTasks(id, watcher, /*watch_start_max=*/true,
|
|
/*watch_end_max=*/true);
|
|
return id;
|
|
}
|
|
|
|
bool NonOverlappingRectanglesEnergyPropagator::BuildAndReportEnergyTooLarge(
|
|
const std::vector<RectangleInRange>& ranges) {
|
|
if (ranges.size() == 2) {
|
|
num_conflicts_two_boxes_++;
|
|
return ClearAndAddTwoBoxesConflictReason(ranges[0].box_index,
|
|
ranges[1].box_index, &x_, &y_);
|
|
}
|
|
x_.ClearReason();
|
|
y_.ClearReason();
|
|
for (const auto& range : ranges) {
|
|
const int b = range.box_index;
|
|
|
|
x_.AddStartMinReason(b, range.bounding_area.x_min);
|
|
y_.AddStartMinReason(b, range.bounding_area.y_min);
|
|
|
|
x_.AddStartMaxReason(b, range.bounding_area.x_max - range.x_size);
|
|
y_.AddStartMaxReason(b, range.bounding_area.y_max - range.y_size);
|
|
|
|
x_.AddSizeMinReason(b);
|
|
y_.AddSizeMinReason(b);
|
|
|
|
x_.AddPresenceReason(b);
|
|
y_.AddPresenceReason(b);
|
|
}
|
|
x_.ImportOtherReasons(y_);
|
|
return x_.ReportConflict();
|
|
}
|
|
|
|
namespace {
|
|
|
|
// We want for different propagation to reuse as much as possible the same
|
|
// line. The idea behind this is to compute the 'canonical' line to use
|
|
// when explaining that boxes overlap on the 'y_dim' dimension. We compute
|
|
// the multiple of the biggest power of two that is common to all boxes.
|
|
IntegerValue FindCanonicalValue(IntegerValue lb, IntegerValue ub) {
|
|
if (lb == ub) return lb;
|
|
if (lb <= 0 && ub > 0) return IntegerValue(0);
|
|
if (lb < 0 && ub <= 0) {
|
|
return -FindCanonicalValue(-ub, -lb);
|
|
}
|
|
|
|
int64_t mask = 0;
|
|
IntegerValue candidate = ub;
|
|
for (int o = 0; o < 62; ++o) {
|
|
mask = 2 * mask + 1;
|
|
const IntegerValue masked_ub(ub.value() & ~mask);
|
|
if (masked_ub >= lb) {
|
|
candidate = masked_ub;
|
|
} else {
|
|
break;
|
|
}
|
|
}
|
|
return candidate;
|
|
}
|
|
|
|
void SplitDisjointBoxes(const SchedulingConstraintHelper& x,
|
|
absl::Span<int> boxes,
|
|
std::vector<absl::Span<int>>* result) {
|
|
result->clear();
|
|
std::sort(boxes.begin(), boxes.end(), [&x](int a, int b) {
|
|
return x.ShiftedStartMin(a) < x.ShiftedStartMin(b);
|
|
});
|
|
int current_start = 0;
|
|
std::size_t current_length = 1;
|
|
IntegerValue current_max_end = x.EndMax(boxes[0]);
|
|
|
|
for (int b = 1; b < boxes.size(); ++b) {
|
|
const int box = boxes[b];
|
|
if (x.ShiftedStartMin(box) < current_max_end) {
|
|
// Merge.
|
|
current_length++;
|
|
current_max_end = std::max(current_max_end, x.EndMax(box));
|
|
} else {
|
|
if (current_length > 1) { // Ignore lists of size 1.
|
|
result->emplace_back(&boxes[current_start], current_length);
|
|
}
|
|
current_start = b;
|
|
current_length = 1;
|
|
current_max_end = x.EndMax(box);
|
|
}
|
|
}
|
|
|
|
// Push last span.
|
|
if (current_length > 1) {
|
|
result->emplace_back(&boxes[current_start], current_length);
|
|
}
|
|
}
|
|
|
|
// This function assumes that the left and right boxes overlap on the second
|
|
// dimension, and that left cannot be after right.
|
|
// It checks and pushes the lower bound of the right box and the upper bound
|
|
// of the left box if need.
|
|
//
|
|
// If y is not null, it import the mandatory reason for the overlap on y in
|
|
// the x helper.
|
|
bool LeftBoxBeforeRightBoxOnFirstDimension(int left, int right,
|
|
SchedulingConstraintHelper* x,
|
|
SchedulingConstraintHelper* y) {
|
|
// left box2 pushes right box2.
|
|
const IntegerValue left_end_min = x->EndMin(left);
|
|
if (left_end_min > x->StartMin(right)) {
|
|
x->ClearReason();
|
|
x->AddPresenceReason(left);
|
|
x->AddPresenceReason(right);
|
|
x->AddReasonForBeingBefore(left, right);
|
|
x->AddEndMinReason(left, left_end_min);
|
|
if (y != nullptr) {
|
|
// left and right must overlap on y.
|
|
ClearAndAddMandatoryOverlapReason(left, right, y);
|
|
// Propagate with the complete reason.
|
|
x->ImportOtherReasons(*y);
|
|
}
|
|
RETURN_IF_FALSE(x->IncreaseStartMin(right, left_end_min));
|
|
}
|
|
|
|
// right box2 pushes left box2.
|
|
const IntegerValue right_start_max = x->StartMax(right);
|
|
if (right_start_max < x->EndMax(left)) {
|
|
x->ClearReason();
|
|
x->AddPresenceReason(left);
|
|
x->AddPresenceReason(right);
|
|
x->AddReasonForBeingBefore(left, right);
|
|
x->AddStartMaxReason(right, right_start_max);
|
|
if (y != nullptr) {
|
|
// left and right must overlap on y.
|
|
ClearAndAddMandatoryOverlapReason(left, right, y);
|
|
// Propagate with the complete reason.
|
|
x->ImportOtherReasons(*y);
|
|
}
|
|
RETURN_IF_FALSE(x->DecreaseEndMax(left, right_start_max));
|
|
}
|
|
|
|
return true;
|
|
}
|
|
|
|
} // namespace
|
|
|
|
// Note that x_ and y_ must be initialized with enough intervals when passed
|
|
// to the disjunctive propagators.
|
|
NonOverlappingRectanglesDisjunctivePropagator::
|
|
NonOverlappingRectanglesDisjunctivePropagator(SchedulingConstraintHelper* x,
|
|
SchedulingConstraintHelper* y,
|
|
Model* model)
|
|
: global_x_(*x),
|
|
global_y_(*y),
|
|
x_(x->NumTasks(), model),
|
|
watcher_(model->GetOrCreate<GenericLiteralWatcher>()),
|
|
overload_checker_(&x_),
|
|
forward_detectable_precedences_(true, &x_),
|
|
backward_detectable_precedences_(false, &x_),
|
|
forward_not_last_(true, &x_),
|
|
backward_not_last_(false, &x_),
|
|
forward_edge_finding_(true, &x_),
|
|
backward_edge_finding_(false, &x_) {}
|
|
|
|
NonOverlappingRectanglesDisjunctivePropagator::
|
|
~NonOverlappingRectanglesDisjunctivePropagator() = default;
|
|
|
|
void NonOverlappingRectanglesDisjunctivePropagator::Register(
|
|
int fast_priority, int slow_priority) {
|
|
fast_id_ = watcher_->Register(this);
|
|
watcher_->SetPropagatorPriority(fast_id_, fast_priority);
|
|
global_x_.WatchAllTasks(fast_id_, watcher_);
|
|
global_y_.WatchAllTasks(fast_id_, watcher_);
|
|
|
|
// This propagator is the one making sure our propagation is complete, so
|
|
// we do need to make sure it is called again if it modified some bounds.
|
|
watcher_->NotifyThatPropagatorMayNotReachFixedPointInOnePass(fast_id_);
|
|
|
|
const int slow_id = watcher_->Register(this);
|
|
watcher_->SetPropagatorPriority(slow_id, slow_priority);
|
|
global_x_.WatchAllTasks(slow_id, watcher_);
|
|
global_y_.WatchAllTasks(slow_id, watcher_);
|
|
}
|
|
|
|
bool NonOverlappingRectanglesDisjunctivePropagator::
|
|
FindBoxesThatMustOverlapAHorizontalLineAndPropagate(
|
|
bool fast_propagation, const SchedulingConstraintHelper& x,
|
|
SchedulingConstraintHelper* y) {
|
|
// Note that since we only push bounds on x, we cache the value for y just
|
|
// once.
|
|
if (!y->SynchronizeAndSetTimeDirection(true)) return false;
|
|
|
|
// Compute relevant boxes, the one with a mandatory part of y. Because we will
|
|
// need to sort it this way, we consider them by increasing start max.
|
|
indexed_boxes_.clear();
|
|
const auto temp = y->TaskByDecreasingStartMax();
|
|
for (int i = temp.size(); --i >= 0;) {
|
|
const int box = temp[i].task_index;
|
|
// Ignore absent boxes.
|
|
if (x.IsAbsent(box) || y->IsAbsent(box)) continue;
|
|
|
|
// Ignore boxes where the relevant presence literal is only on the y
|
|
// dimension, or if both intervals are optionals with different literals.
|
|
if (x.IsPresent(box) && !y->IsPresent(box)) continue;
|
|
if (!x.IsPresent(box) && !y->IsPresent(box) &&
|
|
x.PresenceLiteral(box) != y->PresenceLiteral(box)) {
|
|
continue;
|
|
}
|
|
|
|
const IntegerValue start_max = temp[i].time;
|
|
const IntegerValue end_min = y->EndMin(box);
|
|
if (start_max < end_min) {
|
|
indexed_boxes_.push_back({box, start_max, end_min});
|
|
}
|
|
}
|
|
|
|
// Less than 2 boxes, no propagation.
|
|
if (indexed_boxes_.size() < 2) return true;
|
|
ConstructOverlappingSets(/*already_sorted=*/true, &indexed_boxes_,
|
|
&events_overlapping_boxes_);
|
|
|
|
// Split lists of boxes into disjoint set of boxes (w.r.t. overlap).
|
|
boxes_to_propagate_.clear();
|
|
reduced_overlapping_boxes_.clear();
|
|
for (int i = 0; i < events_overlapping_boxes_.size(); ++i) {
|
|
SplitDisjointBoxes(x, absl::MakeSpan(events_overlapping_boxes_[i]),
|
|
&disjoint_boxes_);
|
|
for (absl::Span<int> sub_boxes : disjoint_boxes_) {
|
|
// Boxes are sorted in a stable manner in the Split method.
|
|
// Note that we do not use reduced_overlapping_boxes_ directly so that
|
|
// the order of iteration is deterministic.
|
|
const auto& insertion = reduced_overlapping_boxes_.insert(sub_boxes);
|
|
if (insertion.second) boxes_to_propagate_.push_back(sub_boxes);
|
|
}
|
|
}
|
|
|
|
// And finally propagate.
|
|
//
|
|
// TODO(user): Sorting of boxes seems influential on the performance. Test.
|
|
for (const absl::Span<const int> boxes : boxes_to_propagate_) {
|
|
// The case of two boxes should be taken care of during "fast" propagation,
|
|
// so we can skip it here.
|
|
if (!fast_propagation && boxes.size() <= 2) continue;
|
|
|
|
x_.ClearOtherHelper();
|
|
if (!x_.ResetFromSubset(x, boxes)) return false;
|
|
|
|
// Collect the common overlapping coordinates of all boxes.
|
|
IntegerValue lb(std::numeric_limits<int64_t>::min());
|
|
IntegerValue ub(std::numeric_limits<int64_t>::max());
|
|
for (const int b : boxes) {
|
|
lb = std::max(lb, y->StartMax(b));
|
|
ub = std::min(ub, y->EndMin(b) - 1);
|
|
}
|
|
CHECK_LE(lb, ub);
|
|
|
|
// We want for different propagation to reuse as much as possible the same
|
|
// line. The idea behind this is to compute the 'canonical' line to use
|
|
// when explaining that boxes overlap on the 'y_dim' dimension. We compute
|
|
// the multiple of the biggest power of two that is common to all boxes.
|
|
//
|
|
// TODO(user): We should scan the integer trail to find the oldest
|
|
// non-empty common interval. Then we can pick the canonical value within
|
|
// it.
|
|
const IntegerValue line_to_use_for_reason = FindCanonicalValue(lb, ub);
|
|
|
|
// Setup x_dim for propagation.
|
|
x_.SetOtherHelper(y, boxes, line_to_use_for_reason);
|
|
|
|
if (fast_propagation) {
|
|
if (x_.NumTasks() == 2) {
|
|
// In that case, we can use simpler algorithms.
|
|
// Note that this case happens frequently (~30% of all calls to this
|
|
// method according to our tests).
|
|
RETURN_IF_FALSE(PropagateOnXWhenOnlyTwoBoxes());
|
|
} else {
|
|
RETURN_IF_FALSE(overload_checker_.Propagate());
|
|
RETURN_IF_FALSE(forward_detectable_precedences_.Propagate());
|
|
RETURN_IF_FALSE(backward_detectable_precedences_.Propagate());
|
|
}
|
|
} else {
|
|
DCHECK_GT(x_.NumTasks(), 2);
|
|
RETURN_IF_FALSE(forward_not_last_.Propagate());
|
|
RETURN_IF_FALSE(backward_not_last_.Propagate());
|
|
RETURN_IF_FALSE(backward_edge_finding_.Propagate());
|
|
RETURN_IF_FALSE(forward_edge_finding_.Propagate());
|
|
}
|
|
}
|
|
|
|
return true;
|
|
}
|
|
|
|
bool NonOverlappingRectanglesDisjunctivePropagator::Propagate() {
|
|
global_x_.SetTimeDirection(true);
|
|
global_y_.SetTimeDirection(true);
|
|
|
|
// Note that the code assumes that this was registered twice in fast and slow
|
|
// mode. So we will not redo some propagation in slow mode that was already
|
|
// done by the fast mode.
|
|
const bool fast_propagation = watcher_->GetCurrentId() == fast_id_;
|
|
RETURN_IF_FALSE(FindBoxesThatMustOverlapAHorizontalLineAndPropagate(
|
|
fast_propagation, global_x_, &global_y_));
|
|
|
|
// We can actually swap dimensions to propagate vertically.
|
|
RETURN_IF_FALSE(FindBoxesThatMustOverlapAHorizontalLineAndPropagate(
|
|
fast_propagation, global_y_, &global_x_));
|
|
|
|
return true;
|
|
}
|
|
|
|
// Specialized propagation on only two boxes that must intersect with the
|
|
// given y_line_for_reason.
|
|
bool NonOverlappingRectanglesDisjunctivePropagator::
|
|
PropagateOnXWhenOnlyTwoBoxes() {
|
|
if (!x_.IsPresent(0) || !x_.IsPresent(1)) return true;
|
|
|
|
// For each direction and each order, we test if the boxes can be disjoint.
|
|
const int state =
|
|
(x_.EndMin(0) <= x_.StartMax(1)) + 2 * (x_.EndMin(1) <= x_.StartMax(0));
|
|
switch (state) {
|
|
case 0: { // Conflict.
|
|
ClearAndAddMandatoryOverlapReason(0, 1, &x_);
|
|
// Note that the secondary helper is set on x.
|
|
return x_.ReportConflict();
|
|
}
|
|
case 1: { // b1 is left of b2.
|
|
return LeftBoxBeforeRightBoxOnFirstDimension(0, 1, &x_, /*y=*/nullptr);
|
|
}
|
|
case 2: { // b2 is left of b1.
|
|
return LeftBoxBeforeRightBoxOnFirstDimension(1, 0, &x_, /*y=*/nullptr);
|
|
}
|
|
default: { // Nothing to deduce.
|
|
return true;
|
|
}
|
|
}
|
|
}
|
|
|
|
int RectanglePairwisePropagator::RegisterWith(GenericLiteralWatcher* watcher) {
|
|
const int id = watcher->Register(this);
|
|
global_x_.WatchAllTasks(id, watcher, /*watch_start_max=*/true,
|
|
/*watch_end_max=*/false);
|
|
global_y_.WatchAllTasks(id, watcher, /*watch_start_max=*/true,
|
|
/*watch_end_max=*/false);
|
|
watcher->NotifyThatPropagatorMayNotReachFixedPointInOnePass(id);
|
|
return id;
|
|
}
|
|
|
|
RectanglePairwisePropagator::~RectanglePairwisePropagator() {
|
|
if (!VLOG_IS_ON(1)) return;
|
|
std::vector<std::pair<std::string, int64_t>> stats;
|
|
stats.push_back({"RectanglePairwisePropagator/called", num_calls_});
|
|
stats.push_back({"RectanglePairwisePropagator/pairwise_conflicts",
|
|
num_pairwise_conflicts_});
|
|
stats.push_back({"RectanglePairwisePropagator/pairwise_propagations",
|
|
num_pairwise_propagations_});
|
|
|
|
shared_stats_->AddStats(stats);
|
|
}
|
|
|
|
bool RectanglePairwisePropagator::Propagate() {
|
|
if (!global_x_.SynchronizeAndSetTimeDirection(true)) return false;
|
|
if (!global_y_.SynchronizeAndSetTimeDirection(true)) return false;
|
|
|
|
num_calls_++;
|
|
|
|
horizontal_zero_area_boxes_.clear();
|
|
vertical_zero_area_boxes_.clear();
|
|
point_zero_area_boxes_.clear();
|
|
non_zero_area_boxes_.clear();
|
|
for (int b = 0; b < global_x_.NumTasks(); ++b) {
|
|
if (!global_x_.IsPresent(b) || !global_y_.IsPresent(b)) continue;
|
|
const IntegerValue x_size_max = global_x_.SizeMax(b);
|
|
const IntegerValue y_size_max = global_y_.SizeMax(b);
|
|
ItemForPairwiseRestriction* box;
|
|
if (x_size_max == 0) {
|
|
if (y_size_max == 0) {
|
|
box = &point_zero_area_boxes_.emplace_back();
|
|
} else {
|
|
box = &vertical_zero_area_boxes_.emplace_back();
|
|
}
|
|
} else if (y_size_max == 0) {
|
|
box = &horizontal_zero_area_boxes_.emplace_back();
|
|
} else {
|
|
box = &non_zero_area_boxes_.emplace_back();
|
|
}
|
|
*box = ItemForPairwiseRestriction{.index = b,
|
|
.x = {.start_min = global_x_.StartMin(b),
|
|
.start_max = global_x_.StartMax(b),
|
|
.end_min = global_x_.EndMin(b),
|
|
.end_max = global_x_.EndMax(b)},
|
|
.y = {.start_min = global_y_.StartMin(b),
|
|
.start_max = global_y_.StartMax(b),
|
|
.end_min = global_y_.EndMin(b),
|
|
.end_max = global_y_.EndMax(b)}};
|
|
}
|
|
|
|
std::vector<PairwiseRestriction> restrictions;
|
|
RETURN_IF_FALSE(FindRestrictionsAndPropagateConflict(non_zero_area_boxes_,
|
|
&restrictions));
|
|
|
|
// Check zero area boxes against non-zero area boxes.
|
|
RETURN_IF_FALSE(FindRestrictionsAndPropagateConflict(
|
|
non_zero_area_boxes_, horizontal_zero_area_boxes_, &restrictions));
|
|
RETURN_IF_FALSE(FindRestrictionsAndPropagateConflict(
|
|
non_zero_area_boxes_, vertical_zero_area_boxes_, &restrictions));
|
|
RETURN_IF_FALSE(FindRestrictionsAndPropagateConflict(
|
|
non_zero_area_boxes_, point_zero_area_boxes_, &restrictions));
|
|
|
|
// Check vertical zero area boxes against horizontal zero area boxes.
|
|
RETURN_IF_FALSE(FindRestrictionsAndPropagateConflict(
|
|
vertical_zero_area_boxes_, horizontal_zero_area_boxes_, &restrictions));
|
|
|
|
for (const PairwiseRestriction& restriction : restrictions) {
|
|
RETURN_IF_FALSE(PropagateTwoBoxes(restriction));
|
|
}
|
|
return true;
|
|
}
|
|
|
|
bool RectanglePairwisePropagator::FindRestrictionsAndPropagateConflict(
|
|
const std::vector<ItemForPairwiseRestriction>& items,
|
|
std::vector<PairwiseRestriction>* restrictions) {
|
|
const int max_pairs =
|
|
params_->max_pairs_pairwise_reasoning_in_no_overlap_2d();
|
|
if (items.size() * (items.size() - 1) / 2 > max_pairs) {
|
|
return true;
|
|
}
|
|
AppendPairwiseRestrictions(items, restrictions);
|
|
for (const PairwiseRestriction& restriction : *restrictions) {
|
|
if (restriction.type ==
|
|
PairwiseRestriction::PairwiseRestrictionType::CONFLICT) {
|
|
RETURN_IF_FALSE(PropagateTwoBoxes(restriction));
|
|
}
|
|
}
|
|
return true;
|
|
}
|
|
|
|
bool RectanglePairwisePropagator::FindRestrictionsAndPropagateConflict(
|
|
const std::vector<ItemForPairwiseRestriction>& items1,
|
|
const std::vector<ItemForPairwiseRestriction>& items2,
|
|
std::vector<PairwiseRestriction>* restrictions) {
|
|
const int max_pairs =
|
|
params_->max_pairs_pairwise_reasoning_in_no_overlap_2d();
|
|
if (items1.size() * items2.size() > max_pairs) {
|
|
return true;
|
|
}
|
|
AppendPairwiseRestrictions(items1, items2, restrictions);
|
|
for (const PairwiseRestriction& restriction : *restrictions) {
|
|
if (restriction.type ==
|
|
PairwiseRestriction::PairwiseRestrictionType::CONFLICT) {
|
|
RETURN_IF_FALSE(PropagateTwoBoxes(restriction));
|
|
}
|
|
}
|
|
return true;
|
|
}
|
|
|
|
bool RectanglePairwisePropagator::PropagateTwoBoxes(
|
|
const PairwiseRestriction& restriction) {
|
|
const int box1 = restriction.first_index;
|
|
const int box2 = restriction.second_index;
|
|
switch (restriction.type) {
|
|
case PairwiseRestriction::PairwiseRestrictionType::CONFLICT:
|
|
num_pairwise_conflicts_++;
|
|
return ClearAndAddTwoBoxesConflictReason(box1, box2, &global_x_,
|
|
&global_y_);
|
|
case PairwiseRestriction::PairwiseRestrictionType::FIRST_LEFT_OF_SECOND:
|
|
num_pairwise_propagations_++;
|
|
return LeftBoxBeforeRightBoxOnFirstDimension(box1, box2, &global_x_,
|
|
&global_y_);
|
|
case PairwiseRestriction::PairwiseRestrictionType::FIRST_RIGHT_OF_SECOND:
|
|
num_pairwise_propagations_++;
|
|
return LeftBoxBeforeRightBoxOnFirstDimension(box2, box1, &global_x_,
|
|
&global_y_);
|
|
case PairwiseRestriction::PairwiseRestrictionType::FIRST_BELOW_SECOND:
|
|
num_pairwise_propagations_++;
|
|
return LeftBoxBeforeRightBoxOnFirstDimension(box1, box2, &global_y_,
|
|
&global_x_);
|
|
case PairwiseRestriction::PairwiseRestrictionType::FIRST_ABOVE_SECOND:
|
|
num_pairwise_propagations_++;
|
|
return LeftBoxBeforeRightBoxOnFirstDimension(box2, box1, &global_y_,
|
|
&global_x_);
|
|
}
|
|
}
|
|
|
|
#undef RETURN_IF_FALSE
|
|
} // namespace sat
|
|
} // namespace operations_research
|