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precedences.cc
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precedences.cc
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// Copyright 2010-2018 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.
#include "ortools/sat/precedences.h"
#include <algorithm>
#include <memory>
#include "ortools/base/cleanup.h"
#include "ortools/base/logging.h"
#include "ortools/base/stl_util.h"
#include "ortools/sat/clause.h"
#include "ortools/sat/cp_constraints.h"
namespace operations_research {
namespace sat {
namespace {
void AppendLowerBoundReasonIfValid(IntegerVariable var,
const IntegerTrail& i_trail,
std::vector<IntegerLiteral>* reason) {
if (var != kNoIntegerVariable) {
reason->push_back(i_trail.LowerBoundAsLiteral(var));
}
}
} // namespace
bool PrecedencesPropagator::Propagate(Trail* trail) { return Propagate(); }
bool PrecedencesPropagator::Propagate() {
while (propagation_trail_index_ < trail_->Index()) {
const Literal literal = (*trail_)[propagation_trail_index_++];
if (literal.Index() >= literal_to_new_impacted_arcs_.size()) continue;
// IMPORTANT: Because of the way Untrail() work, we need to add all the
// potential arcs before we can abort. It is why we iterate twice here.
for (const ArcIndex arc_index :
literal_to_new_impacted_arcs_[literal.Index()]) {
if (--arc_counts_[arc_index] == 0) {
const ArcInfo& arc = arcs_[arc_index];
impacted_arcs_[arc.tail_var].push_back(arc_index);
}
}
// Iterate again to check for a propagation and indirectly update
// modified_vars_.
for (const ArcIndex arc_index :
literal_to_new_impacted_arcs_[literal.Index()]) {
if (arc_counts_[arc_index] > 0) continue;
const ArcInfo& arc = arcs_[arc_index];
if (integer_trail_->IsCurrentlyIgnored(arc.head_var)) continue;
const IntegerValue new_head_lb =
integer_trail_->LowerBound(arc.tail_var) + ArcOffset(arc);
if (new_head_lb > integer_trail_->LowerBound(arc.head_var)) {
if (!EnqueueAndCheck(arc, new_head_lb, trail_)) return false;
}
}
}
// Do the actual propagation of the IntegerVariable bounds.
InitializeBFQueueWithModifiedNodes();
if (!BellmanFordTarjan(trail_)) return false;
// We can only test that no propagation is left if we didn't enqueue new
// literal in the presence of optional variables.
if (propagation_trail_index_ == trail_->Index()) {
DCHECK(NoPropagationLeft(*trail_));
}
// Propagate the presence literals of the arcs that can't be added.
PropagateOptionalArcs(trail_);
// Clean-up modified_vars_ to do as little as possible on the next call.
modified_vars_.ClearAndResize(integer_trail_->NumIntegerVariables());
return true;
}
bool PrecedencesPropagator::PropagateOutgoingArcs(IntegerVariable var) {
for (const ArcIndex arc_index : impacted_arcs_[var]) {
const ArcInfo& arc = arcs_[arc_index];
if (integer_trail_->IsCurrentlyIgnored(arc.head_var)) continue;
const IntegerValue new_head_lb =
integer_trail_->LowerBound(arc.tail_var) + ArcOffset(arc);
if (new_head_lb > integer_trail_->LowerBound(arc.head_var)) {
if (!EnqueueAndCheck(arc, new_head_lb, trail_)) return false;
}
}
return true;
}
void PrecedencesPropagator::Untrail(const Trail& trail, int trail_index) {
if (propagation_trail_index_ > trail_index) {
// This means that we already propagated all there is to propagate
// at the level trail_index, so we can safely clear modified_vars_ in case
// it wasn't already done.
modified_vars_.ClearAndResize(integer_trail_->NumIntegerVariables());
}
while (propagation_trail_index_ > trail_index) {
const Literal literal = trail[--propagation_trail_index_];
if (literal.Index() >= literal_to_new_impacted_arcs_.size()) continue;
for (const ArcIndex arc_index :
literal_to_new_impacted_arcs_[literal.Index()]) {
if (arc_counts_[arc_index]++ == 0) {
const ArcInfo& arc = arcs_[arc_index];
impacted_arcs_[arc.tail_var].pop_back();
}
}
}
}
// Instead of simply sorting the IntegerPrecedences returned by .var,
// experiments showed that it is faster to regroup all the same .var "by hand"
// by first computing how many times they appear and then apply the sorting
// permutation.
void PrecedencesPropagator::ComputePrecedences(
const std::vector<IntegerVariable>& vars,
std::vector<IntegerPrecedences>* output) {
tmp_sorted_vars_.clear();
tmp_precedences_.clear();
for (int index = 0; index < vars.size(); ++index) {
const IntegerVariable var = vars[index];
CHECK_NE(kNoIntegerVariable, var);
if (var >= impacted_arcs_.size()) continue;
for (const ArcIndex arc_index : impacted_arcs_[var]) {
const ArcInfo& arc = arcs_[arc_index];
if (integer_trail_->IsCurrentlyIgnored(arc.head_var)) continue;
IntegerValue offset = arc.offset;
if (arc.offset_var != kNoIntegerVariable) {
offset += integer_trail_->LowerBound(arc.offset_var);
}
// TODO(user): it seems better to ignore negative min offset as we will
// often have relation of the form interval_start >= interval_end -
// offset, and such relation are usually not useful. Revisit this in case
// we see problems where we can propagate more without this test.
if (offset < 0) continue;
if (var_to_degree_[arc.head_var] == 0) {
tmp_sorted_vars_.push_back(
{arc.head_var, integer_trail_->LowerBound(arc.head_var)});
} else {
// This "seen" mechanism is needed because we may have multi-arc and we
// don't want any duplicates in the "is_before" relation. Note that it
// works because var_to_last_index_ is reset by the var_to_degree_ == 0
// case.
if (var_to_last_index_[arc.head_var] == index) continue;
}
var_to_last_index_[arc.head_var] = index;
var_to_degree_[arc.head_var]++;
tmp_precedences_.push_back(
{index, arc.head_var, arc_index.value(), offset});
}
}
// This order is a topological order for the precedences relation order
// provided that all the offset between the involved IntegerVariable are
// positive.
//
// TODO(user): use an order that is always topological? This is not clear
// since it may be slower to compute and not worth it because the order below
// is more natural and may work better.
std::sort(tmp_sorted_vars_.begin(), tmp_sorted_vars_.end());
// Permute tmp_precedences_ into the output to put it in the correct order.
// For that we transform var_to_degree_ to point to the first position of
// each lbvar in the output vector.
int start = 0;
for (const SortedVar pair : tmp_sorted_vars_) {
const int degree = var_to_degree_[pair.var];
if (degree > 1) {
var_to_degree_[pair.var] = start;
start += degree;
} else {
// Optimization: we remove degree one relations.
var_to_degree_[pair.var] = -1;
}
}
output->resize(start);
for (const IntegerPrecedences& precedence : tmp_precedences_) {
if (var_to_degree_[precedence.var] < 0) continue;
(*output)[var_to_degree_[precedence.var]++] = precedence;
}
// Cleanup var_to_degree_, note that we don't need to clean
// var_to_last_index_.
for (const SortedVar pair : tmp_sorted_vars_) {
var_to_degree_[pair.var] = 0;
}
}
void PrecedencesPropagator::AddPrecedenceReason(
int arc_index, IntegerValue min_offset,
std::vector<Literal>* literal_reason,
std::vector<IntegerLiteral>* integer_reason) const {
const ArcInfo& arc = arcs_[ArcIndex(arc_index)];
for (const Literal l : arc.presence_literals) {
literal_reason->push_back(l.Negated());
}
if (arc.offset_var != kNoIntegerVariable) {
// Reason for ArcOffset(arc) to be >= min_offset.
integer_reason->push_back(IntegerLiteral::GreaterOrEqual(
arc.offset_var, min_offset - arc.offset));
}
}
void PrecedencesPropagator::AdjustSizeFor(IntegerVariable i) {
const int index = std::max(i.value(), NegationOf(i).value());
if (index >= impacted_arcs_.size()) {
// TODO(user): only watch lower bound of the relevant variable instead
// of watching everything in [0, max_index_of_variable_used_in_this_class).
for (IntegerVariable var(impacted_arcs_.size()); var <= index; ++var) {
watcher_->WatchLowerBound(var, watcher_id_);
}
impacted_arcs_.resize(index + 1);
impacted_potential_arcs_.resize(index + 1);
var_to_degree_.resize(index + 1);
var_to_last_index_.resize(index + 1);
}
}
void PrecedencesPropagator::AddArc(
IntegerVariable tail, IntegerVariable head, IntegerValue offset,
IntegerVariable offset_var, absl::Span<const Literal> presence_literals) {
DCHECK_EQ(trail_->CurrentDecisionLevel(), 0);
AdjustSizeFor(tail);
AdjustSizeFor(head);
if (offset_var != kNoIntegerVariable) AdjustSizeFor(offset_var);
// This arc is present iff all the literals here are true.
absl::InlinedVector<Literal, 6> enforcement_literals;
{
for (const Literal l : presence_literals) {
enforcement_literals.push_back(l);
}
if (integer_trail_->IsOptional(tail)) {
enforcement_literals.push_back(
integer_trail_->IsIgnoredLiteral(tail).Negated());
}
if (integer_trail_->IsOptional(head)) {
enforcement_literals.push_back(
integer_trail_->IsIgnoredLiteral(head).Negated());
}
if (offset_var != kNoIntegerVariable &&
integer_trail_->IsOptional(offset_var)) {
enforcement_literals.push_back(
integer_trail_->IsIgnoredLiteral(offset_var).Negated());
}
gtl::STLSortAndRemoveDuplicates(&enforcement_literals);
int new_size = 0;
for (const Literal l : enforcement_literals) {
if (trail_->Assignment().LiteralIsTrue(Literal(l))) {
continue; // At true, ignore this literal.
} else if (trail_->Assignment().LiteralIsFalse(Literal(l))) {
return; // At false, ignore completely this arc.
}
enforcement_literals[new_size++] = l;
}
enforcement_literals.resize(new_size);
}
if (head == tail) {
// A self-arc is either plain SAT or plain UNSAT or it forces something on
// the given offset_var or presence_literal_index. In any case it could be
// presolved in something more efficent.
VLOG(1) << "Self arc! This could be presolved. "
<< "var:" << tail << " offset:" << offset
<< " offset_var:" << offset_var
<< " conditioned_by:" << presence_literals;
}
// Remove the offset_var if it is fixed.
// TODO(user): We should also handle the case where tail or head is fixed.
if (offset_var != kNoIntegerVariable) {
const IntegerValue lb = integer_trail_->LowerBound(offset_var);
if (lb == integer_trail_->UpperBound(offset_var)) {
offset += lb;
offset_var = kNoIntegerVariable;
}
}
// Deal first with impacted_potential_arcs_/potential_arcs_.
if (!enforcement_literals.empty()) {
const OptionalArcIndex arc_index(potential_arcs_.size());
potential_arcs_.push_back(
{tail, head, offset, offset_var, enforcement_literals});
impacted_potential_arcs_[tail].push_back(arc_index);
impacted_potential_arcs_[NegationOf(head)].push_back(arc_index);
if (offset_var != kNoIntegerVariable) {
impacted_potential_arcs_[offset_var].push_back(arc_index);
}
}
// Now deal with impacted_arcs_/arcs_.
struct InternalArc {
IntegerVariable tail_var;
IntegerVariable head_var;
IntegerVariable offset_var;
};
std::vector<InternalArc> to_add;
if (offset_var == kNoIntegerVariable) {
// a + offset <= b and -b + offset <= -a
to_add.push_back({tail, head, kNoIntegerVariable});
to_add.push_back({NegationOf(head), NegationOf(tail), kNoIntegerVariable});
} else {
// tail (a) and offset_var (b) are symmetric, so we add:
// - a + b + offset <= c
to_add.push_back({tail, head, offset_var});
to_add.push_back({offset_var, head, tail});
// - a - c + offset <= -b
to_add.push_back({tail, NegationOf(offset_var), NegationOf(head)});
to_add.push_back({NegationOf(head), NegationOf(offset_var), tail});
// - b - c + offset <= -a
to_add.push_back({offset_var, NegationOf(tail), NegationOf(head)});
to_add.push_back({NegationOf(head), NegationOf(tail), offset_var});
}
for (const InternalArc a : to_add) {
// Since we add a new arc, we will need to consider its tail during the next
// propagation. Note that the size of modified_vars_ will be automatically
// updated when new integer variables are created since we register it with
// IntegerTrail in this class contructor.
//
// TODO(user): Adding arcs and then calling Untrail() before Propagate()
// will cause this mecanism to break. Find a more robust implementation.
//
// TODO(user): In some rare corner case, rescanning the whole list of arc
// leaving tail_var can make AddVar() have a quadratic complexity where it
// shouldn't. A better solution would be to see if this new arc currently
// propagate something, and if it does, just update the lower bound of
// a.head_var and let the normal "is modified" mecanism handle any eventual
// follow up propagations.
modified_vars_.Set(a.tail_var);
// If a.head_var is optional, we can potentially remove some literal from
// enforcement_literals.
const ArcIndex arc_index(arcs_.size());
arcs_.push_back(
{a.tail_var, a.head_var, offset, a.offset_var, enforcement_literals});
auto& presence_literals = arcs_.back().presence_literals;
if (integer_trail_->IsOptional(a.head_var)) {
// TODO(user): More generally, we can remove any literal that is implied
// by to_remove.
const Literal to_remove =
integer_trail_->IsIgnoredLiteral(a.head_var).Negated();
const auto it = std::find(presence_literals.begin(),
presence_literals.end(), to_remove);
if (it != presence_literals.end()) presence_literals.erase(it);
}
if (presence_literals.empty()) {
impacted_arcs_[a.tail_var].push_back(arc_index);
} else {
for (const Literal l : presence_literals) {
if (l.Index() >= literal_to_new_impacted_arcs_.size()) {
literal_to_new_impacted_arcs_.resize(l.Index().value() + 1);
}
literal_to_new_impacted_arcs_[l.Index()].push_back(arc_index);
}
}
arc_counts_.push_back(presence_literals.size());
}
}
// TODO(user): On jobshop problems with a lot of tasks per machine (500), this
// takes up a big chunck of the running time even before we find a solution.
// This is because, for each lower bound changed, we inspect 500 arcs even
// though they will never be propagated because the other bound is still at the
// horizon. Find an even sparser algorithm?
void PrecedencesPropagator::PropagateOptionalArcs(Trail* trail) {
for (const IntegerVariable var : modified_vars_.PositionsSetAtLeastOnce()) {
if (var >= impacted_potential_arcs_.size()) break;
// Note that we can currently check the same ArcInfo up to 3 times, one for
// each of the arc variables: tail, NegationOf(head) and offset_var.
for (const OptionalArcIndex arc_index : impacted_potential_arcs_[var]) {
const ArcInfo& arc = potential_arcs_[arc_index];
int num_not_true = 0;
Literal to_propagate;
for (const Literal l : arc.presence_literals) {
if (!trail->Assignment().LiteralIsTrue(l)) {
++num_not_true;
to_propagate = l;
}
}
if (num_not_true != 1) continue;
if (trail->Assignment().LiteralIsFalse(to_propagate)) continue;
// Test if this arc can be present or not.
// Important arc.tail_var can be different from var here.
const IntegerValue tail_lb = integer_trail_->LowerBound(arc.tail_var);
const IntegerValue head_ub = integer_trail_->UpperBound(arc.head_var);
if (tail_lb + ArcOffset(arc) > head_ub) {
integer_reason_.clear();
integer_reason_.push_back(
integer_trail_->LowerBoundAsLiteral(arc.tail_var));
integer_reason_.push_back(
integer_trail_->UpperBoundAsLiteral(arc.head_var));
AppendLowerBoundReasonIfValid(arc.offset_var, *integer_trail_,
&integer_reason_);
literal_reason_.clear();
for (const Literal l : arc.presence_literals) {
if (l != to_propagate) literal_reason_.push_back(l.Negated());
}
integer_trail_->EnqueueLiteral(to_propagate.Negated(), literal_reason_,
integer_reason_);
}
}
}
}
IntegerValue PrecedencesPropagator::ArcOffset(const ArcInfo& arc) const {
return arc.offset + (arc.offset_var == kNoIntegerVariable
? IntegerValue(0)
: integer_trail_->LowerBound(arc.offset_var));
}
bool PrecedencesPropagator::EnqueueAndCheck(const ArcInfo& arc,
IntegerValue new_head_lb,
Trail* trail) {
DCHECK_GT(new_head_lb, integer_trail_->LowerBound(arc.head_var));
// Compute the reason for new_head_lb.
//
// TODO(user): do like for clause and keep the negation of
// arc.presence_literals? I think we could change the integer.h API to accept
// true literal like for IntegerVariable, it is really confusing currently.
literal_reason_.clear();
for (const Literal l : arc.presence_literals) {
literal_reason_.push_back(l.Negated());
}
integer_reason_.clear();
integer_reason_.push_back(integer_trail_->LowerBoundAsLiteral(arc.tail_var));
AppendLowerBoundReasonIfValid(arc.offset_var, *integer_trail_,
&integer_reason_);
// The code works without this block since Enqueue() below can already take
// care of conflicts. However, it is better to deal with the conflict
// ourselves because we can be smarter about the reason this way.
//
// The reason for a "precedence" conflict is always a linear reason
// involving the tail lower_bound, the head upper bound and eventually the
// size lower bound. Because of that, we can use the RelaxLinearReason()
// code.
if (new_head_lb > integer_trail_->UpperBound(arc.head_var)) {
const IntegerValue slack =
new_head_lb - integer_trail_->UpperBound(arc.head_var) - 1;
integer_reason_.push_back(
integer_trail_->UpperBoundAsLiteral(arc.head_var));
std::vector<IntegerValue> coeffs(integer_reason_.size(), IntegerValue(1));
integer_trail_->RelaxLinearReason(slack, coeffs, &integer_reason_);
if (!integer_trail_->IsOptional(arc.head_var)) {
return integer_trail_->ReportConflict(literal_reason_, integer_reason_);
} else {
CHECK(!integer_trail_->IsCurrentlyIgnored(arc.head_var));
const Literal l = integer_trail_->IsIgnoredLiteral(arc.head_var);
if (trail->Assignment().LiteralIsFalse(l)) {
literal_reason_.push_back(l);
return integer_trail_->ReportConflict(literal_reason_, integer_reason_);
} else {
integer_trail_->EnqueueLiteral(l, literal_reason_, integer_reason_);
return true;
}
}
}
return integer_trail_->Enqueue(
IntegerLiteral::GreaterOrEqual(arc.head_var, new_head_lb),
literal_reason_, integer_reason_);
}
bool PrecedencesPropagator::NoPropagationLeft(const Trail& trail) const {
const int num_nodes = impacted_arcs_.size();
for (IntegerVariable var(0); var < num_nodes; ++var) {
for (const ArcIndex arc_index : impacted_arcs_[var]) {
const ArcInfo& arc = arcs_[arc_index];
if (integer_trail_->IsCurrentlyIgnored(arc.head_var)) continue;
if (integer_trail_->LowerBound(arc.tail_var) + ArcOffset(arc) >
integer_trail_->LowerBound(arc.head_var)) {
return false;
}
}
}
return true;
}
void PrecedencesPropagator::InitializeBFQueueWithModifiedNodes() {
// Sparse clear of the queue. TODO(user): only use the sparse version if
// queue.size() is small or use SparseBitset.
const int num_nodes = impacted_arcs_.size();
bf_in_queue_.resize(num_nodes, false);
for (const int node : bf_queue_) bf_in_queue_[node] = false;
bf_queue_.clear();
DCHECK(std::none_of(bf_in_queue_.begin(), bf_in_queue_.end(),
[](bool v) { return v; }));
for (const IntegerVariable var : modified_vars_.PositionsSetAtLeastOnce()) {
if (var >= num_nodes) continue;
bf_queue_.push_back(var.value());
bf_in_queue_[var.value()] = true;
}
}
void PrecedencesPropagator::CleanUpMarkedArcsAndParents() {
// To be sparse, we use the fact that each node with a parent must be in
// modified_vars_.
const int num_nodes = impacted_arcs_.size();
for (const IntegerVariable var : modified_vars_.PositionsSetAtLeastOnce()) {
if (var >= num_nodes) continue;
const ArcIndex parent_arc_index = bf_parent_arc_of_[var.value()];
if (parent_arc_index != -1) {
arcs_[parent_arc_index].is_marked = false;
bf_parent_arc_of_[var.value()] = -1;
bf_can_be_skipped_[var.value()] = false;
}
}
DCHECK(std::none_of(bf_parent_arc_of_.begin(), bf_parent_arc_of_.end(),
[](ArcIndex v) { return v != -1; }));
DCHECK(std::none_of(bf_can_be_skipped_.begin(), bf_can_be_skipped_.end(),
[](bool v) { return v; }));
}
bool PrecedencesPropagator::DisassembleSubtree(
int source, int target, std::vector<bool>* can_be_skipped) {
// Note that we explore a tree, so we can do it in any order, and the one
// below seems to be the fastest.
tmp_vector_.clear();
tmp_vector_.push_back(source);
while (!tmp_vector_.empty()) {
const int tail = tmp_vector_.back();
tmp_vector_.pop_back();
for (const ArcIndex arc_index : impacted_arcs_[IntegerVariable(tail)]) {
const ArcInfo& arc = arcs_[arc_index];
if (arc.is_marked) {
arc.is_marked = false; // mutable.
if (arc.head_var.value() == target) return true;
DCHECK(!(*can_be_skipped)[arc.head_var.value()]);
(*can_be_skipped)[arc.head_var.value()] = true;
tmp_vector_.push_back(arc.head_var.value());
}
}
}
return false;
}
void PrecedencesPropagator::AnalyzePositiveCycle(
ArcIndex first_arc, Trail* trail, std::vector<Literal>* must_be_all_true,
std::vector<Literal>* literal_reason,
std::vector<IntegerLiteral>* integer_reason) {
must_be_all_true->clear();
literal_reason->clear();
integer_reason->clear();
// Follow bf_parent_arc_of_[] to find the cycle containing first_arc.
const IntegerVariable first_arc_head = arcs_[first_arc].head_var;
ArcIndex arc_index = first_arc;
std::vector<ArcIndex> arc_on_cycle;
// Just to be safe and avoid an infinite loop we use the fact that the maximum
// cycle size on a graph with n nodes is of size n. If we have more in the
// code below, it means first_arc is not part of a cycle according to
// bf_parent_arc_of_[], which should never happen.
const int num_nodes = impacted_arcs_.size();
while (arc_on_cycle.size() <= num_nodes) {
arc_on_cycle.push_back(arc_index);
const ArcInfo& arc = arcs_[arc_index];
if (arc.tail_var == first_arc_head) break;
arc_index = bf_parent_arc_of_[arc.tail_var.value()];
CHECK_NE(arc_index, ArcIndex(-1));
}
CHECK_NE(arc_on_cycle.size(), num_nodes + 1) << "Infinite loop.";
// Compute the reason for this cycle.
IntegerValue sum(0);
for (const ArcIndex arc_index : arc_on_cycle) {
const ArcInfo& arc = arcs_[arc_index];
sum += ArcOffset(arc);
AppendLowerBoundReasonIfValid(arc.offset_var, *integer_trail_,
integer_reason);
for (const Literal l : arc.presence_literals) {
literal_reason->push_back(l.Negated());
}
// If the cycle happens to contain optional variable not yet ignored, then
// it is not a conflict anymore, but we can infer that these variable must
// all be ignored. This is because since we propagated them even if they
// where not present for sure, their presence literal must form a cycle
// together (i.e. they are all absent or present at the same time).
if (integer_trail_->IsOptional(arc.head_var)) {
must_be_all_true->push_back(
integer_trail_->IsIgnoredLiteral(arc.head_var));
}
}
// TODO(user): what if the sum overflow? this is just a check so I guess
// we don't really care, but fix the issue.
CHECK_GT(sum, 0);
}
// Note that in our settings it is important to use an algorithm that tries to
// minimize the number of integer_trail_->Enqueue() as much as possible.
//
// TODO(user): The current algorithm is quite efficient, but there is probably
// still room for improvments.
bool PrecedencesPropagator::BellmanFordTarjan(Trail* trail) {
const int num_nodes = impacted_arcs_.size();
// These vector are reset by CleanUpMarkedArcsAndParents() so resize is ok.
bf_can_be_skipped_.resize(num_nodes, false);
bf_parent_arc_of_.resize(num_nodes, ArcIndex(-1));
const auto cleanup =
::gtl::MakeCleanup([this]() { CleanUpMarkedArcsAndParents(); });
// The queue initialization is done by InitializeBFQueueWithModifiedNodes().
while (!bf_queue_.empty()) {
const int node = bf_queue_.front();
bf_queue_.pop_front();
bf_in_queue_[node] = false;
// TODO(user): we don't need bf_can_be_skipped_ since we can detect this
// if this node has a parent arc which is not marked. Investigate if it is
// faster without the std::vector<bool>.
//
// TODO(user): An alternative algorithm is to remove all these nodes from
// the queue instead of simply marking them. This should also lead to a
// better "relaxation" order of the arcs. It is however a bit more work to
// remove them since we need to track their position.
if (bf_can_be_skipped_[node]) {
DCHECK_NE(bf_parent_arc_of_[node], -1);
DCHECK(!arcs_[bf_parent_arc_of_[node]].is_marked);
continue;
}
const IntegerValue tail_lb =
integer_trail_->LowerBound(IntegerVariable(node));
for (const ArcIndex arc_index : impacted_arcs_[IntegerVariable(node)]) {
const ArcInfo& arc = arcs_[arc_index];
DCHECK_EQ(arc.tail_var, node);
const IntegerValue candidate = tail_lb + ArcOffset(arc);
if (candidate > integer_trail_->LowerBound(arc.head_var)) {
if (integer_trail_->IsCurrentlyIgnored(arc.head_var)) continue;
if (!EnqueueAndCheck(arc, candidate, trail)) return false;
// This is the Tarjan contribution to Bellman-Ford. This code detect
// positive cycle, and because it disassemble the subtree while doing
// so, the cost is amortized during the algorithm execution. Another
// advantages is that it will mark the node explored here as skippable
// which will avoid to propagate them too early (knowing that they will
// need to be propagated again later).
if (DisassembleSubtree(arc.head_var.value(), arc.tail_var.value(),
&bf_can_be_skipped_)) {
std::vector<Literal> must_be_all_true;
AnalyzePositiveCycle(arc_index, trail, &must_be_all_true,
&literal_reason_, &integer_reason_);
if (must_be_all_true.empty()) {
return integer_trail_->ReportConflict(literal_reason_,
integer_reason_);
} else {
gtl::STLSortAndRemoveDuplicates(&must_be_all_true);
for (const Literal l : must_be_all_true) {
if (trail_->Assignment().LiteralIsFalse(l)) {
literal_reason_.push_back(l);
return integer_trail_->ReportConflict(literal_reason_,
integer_reason_);
}
}
for (const Literal l : must_be_all_true) {
if (trail_->Assignment().LiteralIsTrue(l)) continue;
integer_trail_->EnqueueLiteral(l, literal_reason_,
integer_reason_);
}
// We just marked some optional variable as ignored, no need
// to update bf_parent_arc_of_[].
continue;
}
}
// We need to enforce the invariant that only the arc_index in
// bf_parent_arc_of_[] are marked (but not necessarily all of them
// since we unmark some in DisassembleSubtree()).
if (bf_parent_arc_of_[arc.head_var.value()] != -1) {
arcs_[bf_parent_arc_of_[arc.head_var.value()]].is_marked = false;
}
// Tricky: We just enqueued the fact that the lower-bound of head is
// candidate. However, because the domain of head may be discrete, it is
// possible that the lower-bound of head is now higher than candidate!
// If this is the case, we don't update bf_parent_arc_of_[] so that we
// don't wrongly detect a positive weight cycle because of this "extra
// push".
if (integer_trail_->LowerBound(arc.head_var) == candidate) {
bf_parent_arc_of_[arc.head_var.value()] = arc_index;
arcs_[arc_index].is_marked = true;
} else {
// We still unmark any previous dependency, since we have pushed the
// value of arc.head_var further.
bf_parent_arc_of_[arc.head_var.value()] = -1;
}
bf_can_be_skipped_[arc.head_var.value()] = false;
if (!bf_in_queue_[arc.head_var.value()]) {
bf_queue_.push_back(arc.head_var.value());
bf_in_queue_[arc.head_var.value()] = true;
}
}
}
}
return true;
}
int PrecedencesPropagator::AddGreaterThanAtLeastOneOfConstraintsFromClause(
const absl::Span<const Literal> clause, Model* model) {
CHECK_EQ(model->GetOrCreate<Trail>()->CurrentDecisionLevel(), 0);
if (clause.size() < 2) return 0;
// Collect all arcs impacted by this clause.
std::vector<ArcInfo> infos;
for (const Literal l : clause) {
if (l.Index() >= literal_to_new_impacted_arcs_.size()) continue;
for (const ArcIndex arc_index : literal_to_new_impacted_arcs_[l.Index()]) {
const ArcInfo& arc = arcs_[arc_index];
if (arc.presence_literals.size() != 1) continue;
// TODO(user): Support variable offset.
if (arc.offset_var != kNoIntegerVariable) continue;
infos.push_back(arc);
}
}
if (infos.size() <= 1) return 0;
// Stable sort by head_var so that for a same head_var, the entry are sorted
// by Literal as they appear in clause.
std::stable_sort(infos.begin(), infos.end(),
[](const ArcInfo& a, const ArcInfo& b) {
return a.head_var < b.head_var;
});
// We process ArcInfo with the same head_var toghether.
int num_added_constraints = 0;
auto* solver = model->GetOrCreate<SatSolver>();
for (int i = 0; i < infos.size();) {
const int start = i;
const IntegerVariable head_var = infos[start].head_var;
for (i++; i < infos.size() && infos[i].head_var == head_var; ++i) {
}
const absl::Span<ArcInfo> arcs(&infos[start], i - start);
// Skip single arcs since it will already be fully propagated.
if (arcs.size() < 2) continue;
// Heuristic. Look for full or almost full clauses. We could add
// GreaterThanAtLeastOneOf() with more enforcement literals. TODO(user):
// experiments.
if (arcs.size() + 1 < clause.size()) continue;
std::vector<IntegerVariable> vars;
std::vector<IntegerValue> offsets;
std::vector<Literal> selectors;
std::vector<Literal> enforcements;
int j = 0;
for (const Literal l : clause) {
bool added = false;
for (; j < arcs.size() && l == arcs[j].presence_literals.front(); ++j) {
added = true;
vars.push_back(arcs[j].tail_var);
offsets.push_back(arcs[j].offset);
// Note that duplicate selector are supported.
//
// TODO(user): If we support variable offset, we should regroup the arcs
// into one (tail + offset <= head) though, instead of having too
// identical entries.
selectors.push_back(l);
}
if (!added) {
enforcements.push_back(l.Negated());
}
}
// No point adding a constraint if there is not at least two different
// literals in selectors.
if (enforcements.size() + 1 == clause.size()) continue;
++num_added_constraints;
model->Add(GreaterThanAtLeastOneOf(head_var, vars, offsets, selectors,
enforcements));
if (!solver->FinishPropagation()) return num_added_constraints;
}
return num_added_constraints;
}
int PrecedencesPropagator::
AddGreaterThanAtLeastOneOfConstraintsWithClauseAutoDetection(Model* model) {
auto* time_limit = model->GetOrCreate<TimeLimit>();
auto* solver = model->GetOrCreate<SatSolver>();
// Fill the set of incoming conditional arcs for each variables.
gtl::ITIVector<IntegerVariable, std::vector<ArcIndex>> incoming_arcs_;
for (ArcIndex arc_index(0); arc_index < arcs_.size(); ++arc_index) {
const ArcInfo& arc = arcs_[arc_index];
// Only keep arc that have a fixed offset and a single presence_literals.
if (arc.offset_var != kNoIntegerVariable) continue;
if (arc.tail_var == arc.head_var) continue;
if (arc.presence_literals.size() != 1) continue;
if (arc.head_var >= incoming_arcs_.size()) {
incoming_arcs_.resize(arc.head_var.value() + 1);
}
incoming_arcs_[arc.head_var].push_back(arc_index);
}
int num_added_constraints = 0;
for (IntegerVariable target(0); target < incoming_arcs_.size(); ++target) {
if (incoming_arcs_[target].size() <= 1) continue;
if (time_limit->LimitReached()) return num_added_constraints;
// Detect set of incoming arcs for which at least one must be present.
// TODO(user): Find more than one disjoint set of incoming arcs.
// TODO(user): call MinimizeCoreWithPropagation() on the clause.
solver->Backtrack(0);
if (solver->IsModelUnsat()) return num_added_constraints;
std::vector<Literal> clause;
for (const ArcIndex arc_index : incoming_arcs_[target]) {
const Literal literal = arcs_[arc_index].presence_literals.front();
if (solver->Assignment().LiteralIsFalse(literal)) continue;
const int old_level = solver->CurrentDecisionLevel();
solver->EnqueueDecisionAndBacktrackOnConflict(literal.Negated());
if (solver->IsModelUnsat()) return num_added_constraints;
const int new_level = solver->CurrentDecisionLevel();
if (new_level <= old_level) {
clause = solver->GetLastIncompatibleDecisions();
break;
}
}
solver->Backtrack(0);
if (clause.size() > 1) {
// Extract the set of arc for which at least one must be present.
const std::set<Literal> clause_set(clause.begin(), clause.end());
std::vector<ArcIndex> arcs_in_clause;
for (const ArcIndex arc_index : incoming_arcs_[target]) {
const Literal literal(arcs_[arc_index].presence_literals.front());
if (gtl::ContainsKey(clause_set, literal.Negated())) {
arcs_in_clause.push_back(arc_index);
}
}
VLOG(2) << arcs_in_clause.size() << "/" << incoming_arcs_[target].size();
++num_added_constraints;
std::vector<IntegerVariable> vars;
std::vector<IntegerValue> offsets;
std::vector<Literal> selectors;
for (const ArcIndex a : arcs_in_clause) {
vars.push_back(arcs_[a].tail_var);
offsets.push_back(arcs_[a].offset);
selectors.push_back(Literal(arcs_[a].presence_literals.front()));
}
model->Add(GreaterThanAtLeastOneOf(target, vars, offsets, selectors));
if (!solver->FinishPropagation()) return num_added_constraints;
}
}
return num_added_constraints;
}
int PrecedencesPropagator::AddGreaterThanAtLeastOneOfConstraints(Model* model) {
VLOG(1) << "Detecting GreaterThanAtLeastOneOf() constraints...";
auto* time_limit = model->GetOrCreate<TimeLimit>();
auto* solver = model->GetOrCreate<SatSolver>();
auto* clauses = model->GetOrCreate<LiteralWatchers>();
int num_added_constraints = 0;
// We have two possible approaches. For now, we prefer the first one except if
// there is too many clauses in the problem.
//
// TODO(user): Do more extensive experiment. Remove the second approach as
// it is more time consuming? or identify when it make sense. Note that the
// first approach also allows to use "incomplete" at least one between arcs.
if (clauses->AllClausesInCreationOrder().size() < 1e6) {
// TODO(user): This does not take into account clause of size 2 since they
// are stored in the BinaryImplicationGraph instead. Some ideas specific
// to size 2:
// - There can be a lot of such clauses, but it might be nice to consider
// them. we need to experiments.
// - The automatic clause detection might be a better approach and it
// could be combined with probing.
for (const SatClause* clause : clauses->AllClausesInCreationOrder()) {
if (time_limit->LimitReached()) return num_added_constraints;
if (solver->IsModelUnsat()) return num_added_constraints;
num_added_constraints += AddGreaterThanAtLeastOneOfConstraintsFromClause(
clause->AsSpan(), model);
}
} else {
num_added_constraints +=
AddGreaterThanAtLeastOneOfConstraintsWithClauseAutoDetection(model);
}
VLOG(1) << "Added " << num_added_constraints
<< " GreaterThanAtLeastOneOf() constraints.";
return num_added_constraints;
}
} // namespace sat
} // namespace operations_research