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ortools-clone/ortools/sat/integer.h

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// Copyright 2010-2025 Google LLC
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#ifndef OR_TOOLS_SAT_INTEGER_H_
#define OR_TOOLS_SAT_INTEGER_H_
#include <stdlib.h>
#include <algorithm>
#include <cstdint>
#include <deque>
#include <functional>
#include <limits>
#include <string>
#include <utility>
#include <vector>
#include "absl/base/attributes.h"
#include "absl/container/btree_map.h"
#include "absl/container/flat_hash_map.h"
#include "absl/container/inlined_vector.h"
#include "absl/log/check.h"
#include "absl/strings/str_cat.h"
#include "absl/types/span.h"
#include "ortools/base/logging.h"
#include "ortools/base/strong_vector.h"
#include "ortools/sat/integer_base.h"
#include "ortools/sat/model.h"
#include "ortools/sat/sat_base.h"
#include "ortools/sat/sat_parameters.pb.h"
#include "ortools/sat/sat_solver.h"
#include "ortools/util/bitset.h"
#include "ortools/util/rev.h"
#include "ortools/util/sorted_interval_list.h"
#include "ortools/util/strong_integers.h"
#include "ortools/util/time_limit.h"
namespace operations_research {
namespace sat {
using InlinedIntegerLiteralVector = absl::InlinedVector<IntegerLiteral, 2>;
using InlinedIntegerValueVector =
absl::InlinedVector<std::pair<IntegerVariable, IntegerValue>, 2>;
struct LiteralValueValue {
Literal literal;
IntegerValue left_value;
IntegerValue right_value;
// Used for testing.
bool operator==(const LiteralValueValue& rhs) const {
return literal.Index() == rhs.literal.Index() &&
left_value == rhs.left_value && right_value == rhs.right_value;
}
std::string DebugString() const {
return absl::StrCat("(lit(", literal.Index().value(), ") * ",
left_value.value(), " * ", right_value.value(), ")");
}
};
// Sometimes we propagate fact with no reason at a positive level, those
// will automatically be fixed on the next restart.
//
// TODO(user): If we change the logic to not restart right away, we probably
// need to remove duplicates bounds for the same variable.
struct DelayedRootLevelDeduction {
std::vector<Literal> literal_to_fix;
std::vector<IntegerLiteral> integer_literal_to_fix;
};
// Each integer variable x will be associated with a set of literals encoding
// (x >= v) for some values of v. This class maintains the relationship between
// the integer variables and such literals which can be created by a call to
// CreateAssociatedLiteral().
//
// The advantage of creating such Boolean variables is that the SatSolver which
// is driving the search can then take this variable as a decision and maintain
// these variables activity and so on. These variables can also be propagated
// directly by the learned clauses.
//
// This class also support a non-lazy full domain encoding which will create one
// literal per possible value in the domain. See FullyEncodeVariable(). This is
// meant to be called by constraints that directly work on the variable values
// like a table constraint or an all-diff constraint.
//
// TODO(user): We could also lazily create precedences Booleans between two
// arbitrary IntegerVariable. This is better done in the PrecedencesPropagator
// though.
class IntegerEncoder {
public:
explicit IntegerEncoder(Model* model)
: sat_solver_(model->GetOrCreate<SatSolver>()),
trail_(model->GetOrCreate<Trail>()),
delayed_to_fix_(model->GetOrCreate<DelayedRootLevelDeduction>()),
domains_(*model->GetOrCreate<IntegerDomains>()),
num_created_variables_(0) {}
// This type is neither copyable nor movable.
IntegerEncoder(const IntegerEncoder&) = delete;
IntegerEncoder& operator=(const IntegerEncoder&) = delete;
~IntegerEncoder() {
VLOG(1) << "#variables created = " << num_created_variables_;
}
// Memory optimization: you can call this before encoding variables.
void ReserveSpaceForNumVariables(int num_vars);
// Fully encode a variable using its current initial domain.
// If the variable is already fully encoded, this does nothing.
//
// This creates new Booleans variables as needed:
// 1) num_values for the literals X == value. Except when there is just
// two value in which case only one variable is created.
// 2) num_values - 3 for the literals X >= value or X <= value (using their
// negation). The -3 comes from the fact that we can reuse the equality
// literals for the two extreme points.
//
// The encoding for NegationOf(var) is automatically created too. It reuses
// the same Boolean variable as the encoding of var.
//
// TODO(user): It is currently only possible to call that at the decision
// level zero because we cannot add ternary clause in the middle of the
// search (for now). This is Checked.
void FullyEncodeVariable(IntegerVariable var);
// Returns true if we know that PartialDomainEncoding(var) span the full
// domain of var. This is always true if FullyEncodeVariable(var) has been
// called.
bool VariableIsFullyEncoded(IntegerVariable var) const;
// Returns the list of literal <=> var == value currently associated to the
// given variable. The result is sorted by value. We filter literal at false,
// and if a literal is true, then you will get a singleton. To be sure to get
// the full set of encoded value, then you should call this at level zero.
//
// The FullDomainEncoding() just check VariableIsFullyEncoded() and returns
// the same result.
//
// WARNING: The reference returned is only valid until the next call to one
// of these functions.
const std::vector<ValueLiteralPair>& FullDomainEncoding(
IntegerVariable var) const;
const std::vector<ValueLiteralPair>& PartialDomainEncoding(
IntegerVariable var) const;
// Returns the "canonical" (i_lit, negation of i_lit) pair. This mainly
// deal with domain with initial hole like [1,2][5,6] so that if one ask
// for x <= 3, this get canonicalized in the pair (x <= 2, x >= 5).
//
// Note that it is an error to call this with a literal that is trivially true
// or trivially false according to the initial variable domain. This is
// CHECKed to make sure we don't create wasteful literal.
//
// TODO(user): This is linear in the domain "complexity", we can do better if
// needed.
std::pair<IntegerLiteral, IntegerLiteral> Canonicalize(
IntegerLiteral i_lit) const;
// Returns, after creating it if needed, a Boolean literal such that:
// - if true, then the IntegerLiteral is true.
// - if false, then the negated IntegerLiteral is true.
//
// Note that this "canonicalize" the given literal first.
//
// This add the proper implications with the two "neighbor" literals of this
// one if they exist. This is the "list encoding" in: Thibaut Feydy, Peter J.
// Stuckey, "Lazy Clause Generation Reengineered", CP 2009.
Literal GetOrCreateAssociatedLiteral(IntegerLiteral i_lit);
Literal GetOrCreateLiteralAssociatedToEquality(IntegerVariable var,
IntegerValue value);
// Associates the Boolean literal to (X >= bound) or (X == value). If a
// literal was already associated to this fact, this will add an equality
// constraints between both literals. If the fact is trivially true or false,
// this will fix the given literal.
void AssociateToIntegerLiteral(Literal literal, IntegerLiteral i_lit);
void AssociateToIntegerEqualValue(Literal literal, IntegerVariable var,
IntegerValue value);
// Returns kNoLiteralIndex if there is no associated or the associated literal
// otherwise.
//
// Tricky: for domain with hole, like [0,1][5,6], we assume some equivalence
// classes, like >=2, >=3, >=4 are all the same as >= 5.
bool IsFixedOrHasAssociatedLiteral(IntegerLiteral i_lit) const;
LiteralIndex GetAssociatedLiteral(IntegerLiteral i_lit) const;
LiteralIndex GetAssociatedEqualityLiteral(IntegerVariable var,
IntegerValue value) const;
// Advanced usage. It is more efficient to create the associated literals in
// order, but it might be anoying to do so. Instead, you can first call
// DisableImplicationBetweenLiteral() and when you are done creating all the
// associated literals, you can call (only at level zero)
// AddAllImplicationsBetweenAssociatedLiterals() which will also turn back on
// the implications between literals for the one that will be added
// afterwards.
void DisableImplicationBetweenLiteral() { add_implications_ = false; }
void AddAllImplicationsBetweenAssociatedLiterals();
// Returns the IntegerLiterals that were associated with the given Literal.
const InlinedIntegerLiteralVector& GetIntegerLiterals(Literal lit) const {
if (lit.Index() >= reverse_encoding_.size()) {
return empty_integer_literal_vector_;
}
return reverse_encoding_[lit];
}
// Returns the variable == value pairs that were associated with the given
// Literal. Note that only positive IntegerVariable appears here.
const InlinedIntegerValueVector& GetEqualityLiterals(Literal lit) const {
if (lit.Index() >= reverse_equality_encoding_.size()) {
return empty_integer_value_vector_;
}
return reverse_equality_encoding_[lit];
}
// Returns all the variables for which this literal is associated to either
// var >= value or var == value.
const std::vector<IntegerVariable>& GetAllAssociatedVariables(
Literal lit) const {
temp_associated_vars_.clear();
for (const IntegerLiteral l : GetIntegerLiterals(lit)) {
temp_associated_vars_.push_back(l.var);
}
for (const auto& [var, value] : GetEqualityLiterals(lit)) {
temp_associated_vars_.push_back(var);
}
return temp_associated_vars_;
}
// If it exists, returns a [0, 1] integer variable which is equal to 1 iff the
// given literal is true. Returns kNoIntegerVariable if such variable does not
// exist. Note that one can create one by creating a new IntegerVariable and
// calling AssociateToIntegerEqualValue().
//
// Note that this will only return "positive" IntegerVariable.
IntegerVariable GetLiteralView(Literal lit) const {
if (lit.Index() >= literal_view_.size()) return kNoIntegerVariable;
const IntegerVariable result = literal_view_[lit];
DCHECK(result == kNoIntegerVariable || VariableIsPositive(result));
return result;
}
// If this is true, then a literal can be linearized with an affine expression
// involving an integer variable.
ABSL_MUST_USE_RESULT bool LiteralOrNegationHasView(
Literal lit, IntegerVariable* view = nullptr,
bool* view_is_direct = nullptr) const;
// Returns a Boolean literal associated with a bound lower than or equal to
// the one of the given IntegerLiteral. If the given IntegerLiteral is true,
// then the returned literal should be true too. Returns kNoLiteralIndex if no
// such literal was created.
//
// Ex: if 'i' is (x >= 4) and we already created a literal associated to
// (x >= 2) but not to (x >= 3), we will return the literal associated with
// (x >= 2).
LiteralIndex SearchForLiteralAtOrBefore(IntegerLiteral i_lit,
IntegerValue* bound) const;
// Gets the literal always set to true, make it if it does not exist.
Literal GetTrueLiteral() {
if (literal_index_true_ == kNoLiteralIndex) {
DCHECK_EQ(0, sat_solver_->CurrentDecisionLevel());
const Literal literal_true =
Literal(sat_solver_->NewBooleanVariable(), true);
literal_index_true_ = literal_true.Index();
// This might return false if we are already UNSAT.
// TODO(user): Make sure we abort right away on unsat!
(void)sat_solver_->AddUnitClause(literal_true);
}
return Literal(literal_index_true_);
}
Literal GetFalseLiteral() { return GetTrueLiteral().Negated(); }
// Returns the set of Literal associated to IntegerLiteral of the form var >=
// value. We make a copy, because this can be easily invalidated when calling
// any function of this class. So it is less efficient but safer.
std::vector<ValueLiteralPair> PartialGreaterThanEncoding(
IntegerVariable var) const;
// Makes sure all element in the >= encoding are non-trivial and canonical.
// The input variable must be positive.
bool UpdateEncodingOnInitialDomainChange(IntegerVariable var, Domain domain);
private:
// Adds the implications:
// Literal(before) <= associated_lit <= Literal(after).
// Arguments:
// - map is just encoding_by_var_[associated_lit.var] and is passed as a
// slight optimization.
// - 'it' is the current position of associated_lit in map, i.e. we must have
// it->second == associated_lit.
void AddImplications(
const absl::btree_map<IntegerValue, Literal>& map,
absl::btree_map<IntegerValue, Literal>::const_iterator it,
Literal associated_lit);
SatSolver* sat_solver_;
Trail* trail_;
DelayedRootLevelDeduction* delayed_to_fix_;
const IntegerDomains& domains_;
bool add_implications_ = true;
int64_t num_created_variables_ = 0;
// We keep all the literals associated to an Integer variable in a map ordered
// by bound (so we can properly add implications between the literals
// corresponding to the same variable).
//
// Note that we only keep this for positive variable.
// The one for the negation can be infered by it.
//
// Like x >= 1 x >= 4 x >= 5
// Correspond to x <= 0 x <= 3 x <= 4
// That is -x >= 0 -x >= -2 -x >= -4
//
// With potentially stronger <= bound if we fall into domain holes.
//
// TODO(user): Remove the entry no longer needed because of level zero
// propagations.
util_intops::StrongVector<PositiveOnlyIndex,
absl::btree_map<IntegerValue, Literal>>
encoding_by_var_;
// Store for a given LiteralIndex the list of its associated IntegerLiterals.
const InlinedIntegerLiteralVector empty_integer_literal_vector_;
util_intops::StrongVector<LiteralIndex, InlinedIntegerLiteralVector>
reverse_encoding_;
const InlinedIntegerValueVector empty_integer_value_vector_;
util_intops::StrongVector<LiteralIndex, InlinedIntegerValueVector>
reverse_equality_encoding_;
// Used by GetAllAssociatedVariables().
mutable std::vector<IntegerVariable> temp_associated_vars_;
// Store for a given LiteralIndex its IntegerVariable view or kNoVariableIndex
// if there is none. Note that only positive IntegerVariable will appear here.
util_intops::StrongVector<LiteralIndex, IntegerVariable> literal_view_;
// Mapping (variable == value) -> associated literal. Note that even if
// there is more than one literal associated to the same fact, we just keep
// the first one that was added.
//
// Note that we only keep positive IntegerVariable here to reduce memory
// usage.
absl::flat_hash_map<std::pair<PositiveOnlyIndex, IntegerValue>, Literal>
equality_to_associated_literal_;
// Mutable because this is lazily cleaned-up by PartialDomainEncoding().
mutable util_intops::StrongVector<PositiveOnlyIndex,
absl::InlinedVector<ValueLiteralPair, 2>>
equality_by_var_;
// Variables that are fully encoded.
mutable util_intops::StrongVector<PositiveOnlyIndex, bool> is_fully_encoded_;
// A literal that is always true, convenient to encode trivial domains.
// This will be lazily created when needed.
LiteralIndex literal_index_true_ = kNoLiteralIndex;
// Temporary memory used by FullyEncodeVariable().
std::vector<IntegerValue> tmp_values_;
std::vector<ValueLiteralPair> tmp_encoding_;
// Temporary memory for the result of PartialDomainEncoding().
mutable std::vector<ValueLiteralPair> partial_encoding_;
};
class LazyReasonInterface {
public:
LazyReasonInterface() = default;
virtual ~LazyReasonInterface() = default;
// When called, this must fill the two vectors so that literals contains any
// Literal part of the reason and dependencies contains the trail index of any
// IntegerLiteral that is also part of the reason.
//
// Remark: integer_literal[trail_index] might not exist or has nothing to
// do with what was propagated.
//
// TODO(user): {id, propagation_slack, var_to_explain, trail_index} is just a
// generic "payload" and we should probably rename it as such so that each
// implementation can store different things.
virtual void Explain(int id, IntegerValue propagation_slack,
IntegerVariable var_to_explain, int trail_index,
std::vector<Literal>* literals_reason,
std::vector<int>* trail_indices_reason) = 0;
};
// This class maintains a set of integer variables with their current bounds.
// Bounds can be propagated from an external "source" and this class helps
// to maintain the reason for each propagation.
class IntegerTrail final : public SatPropagator {
public:
explicit IntegerTrail(Model* model)
: SatPropagator("IntegerTrail"),
delayed_to_fix_(model->GetOrCreate<DelayedRootLevelDeduction>()),
domains_(model->GetOrCreate<IntegerDomains>()),
encoder_(model->GetOrCreate<IntegerEncoder>()),
trail_(model->GetOrCreate<Trail>()),
sat_solver_(model->GetOrCreate<SatSolver>()),
time_limit_(model->GetOrCreate<TimeLimit>()),
parameters_(*model->GetOrCreate<SatParameters>()) {
model->GetOrCreate<SatSolver>()->AddPropagator(this);
}
// This type is neither copyable nor movable.
IntegerTrail(const IntegerTrail&) = delete;
IntegerTrail& operator=(const IntegerTrail&) = delete;
~IntegerTrail() final;
// SatPropagator interface. These functions make sure the current bounds
// information is in sync with the current solver literal trail. Any
// class/propagator using this class must make sure it is synced to the
// correct state before calling any of its functions.
bool Propagate(Trail* trail) final;
void Untrail(const Trail& trail, int literal_trail_index) final;
absl::Span<const Literal> Reason(const Trail& trail, int trail_index,
int64_t conflict_id) const final;
// Returns the number of created integer variables.
//
// Note that this is twice the number of call to AddIntegerVariable() since
// we automatically create the NegationOf() variable too.
IntegerVariable NumIntegerVariables() const {
return IntegerVariable(var_lbs_.size());
}
// Optimization: you can call this before calling AddIntegerVariable()
// num_vars time.
void ReserveSpaceForNumVariables(int num_vars);
// Adds a new integer variable. Adding integer variable can only be done when
// the decision level is zero (checked). The given bounds are INCLUSIVE and
// must not cross.
//
// Note on integer overflow: 'upper_bound - lower_bound' must fit on an
// int64_t, this is DCHECKed. More generally, depending on the constraints
// that are added, the bounds magnitude must be small enough to satisfy each
// constraint overflow precondition.
IntegerVariable AddIntegerVariable(IntegerValue lower_bound,
IntegerValue upper_bound);
// Same as above but for a more complex domain specified as a sorted list of
// disjoint intervals. See the Domain class.
IntegerVariable AddIntegerVariable(const Domain& domain);
// Returns the initial domain of the given variable. Note that the min/max
// are updated with level zero propagation, but not holes.
const Domain& InitialVariableDomain(IntegerVariable var) const;
// Takes the intersection with the current initial variable domain.
//
// TODO(user): There is some memory inefficiency if this is called many time
// because of the underlying data structure we use. In practice, when used
// with a presolve, this is not often used, so that is fine though.
bool UpdateInitialDomain(IntegerVariable var, Domain domain);
// Same as AddIntegerVariable(value, value), but this is a bit more efficient
// because it reuses another constant with the same value if its exist.
//
// Note(user): Creating constant integer variable is a bit wasteful, but not
// that much, and it allows to simplify a lot of constraints that do not need
// to handle this case any differently than the general one. Maybe there is a
// better solution, but this is not really high priority as of December 2016.
IntegerVariable GetOrCreateConstantIntegerVariable(IntegerValue value);
int NumConstantVariables() const;
// Same as AddIntegerVariable() but uses the maximum possible range. Note
// that since we take negation of bounds in various places, we make sure that
// we don't have overflow when we take the negation of the lower bound or of
// the upper bound.
IntegerVariable AddIntegerVariable() {
return AddIntegerVariable(kMinIntegerValue, kMaxIntegerValue);
}
// Returns the current lower/upper bound of the given integer variable.
IntegerValue LowerBound(IntegerVariable i) const;
IntegerValue UpperBound(IntegerVariable i) const;
// If one needs to do a lot of LowerBound()/UpperBound() it will be faster
// to cache the current pointer to the underlying vector.
const IntegerValue* LowerBoundsData() const { return var_lbs_.data(); }
// Checks if the variable is fixed.
bool IsFixed(IntegerVariable i) const;
// Checks that the variable is fixed and returns its value.
IntegerValue FixedValue(IntegerVariable i) const;
// Same as above for an affine expression.
IntegerValue LowerBound(AffineExpression expr) const;
IntegerValue UpperBound(AffineExpression expr) const;
IntegerValue UpperBound(LinearExpression2 expr) const;
bool IsFixed(AffineExpression expr) const;
IntegerValue FixedValue(AffineExpression expr) const;
// Returns the integer literal that represent the current lower/upper bound of
// the given integer variable.
IntegerLiteral LowerBoundAsLiteral(IntegerVariable i) const;
IntegerLiteral UpperBoundAsLiteral(IntegerVariable i) const;
// Returns the integer literal that represent the current lower/upper bound of
// the given affine expression. In case the expression is constant, it returns
// IntegerLiteral::TrueLiteral().
IntegerLiteral LowerBoundAsLiteral(AffineExpression expr) const;
IntegerLiteral UpperBoundAsLiteral(AffineExpression expr) const;
// Returns the current value (if known) of an IntegerLiteral.
bool IntegerLiteralIsTrue(IntegerLiteral l) const;
bool IntegerLiteralIsFalse(IntegerLiteral l) const;
bool IsTrueAtLevelZero(IntegerLiteral l) const;
// Returns globally valid lower/upper bound on the given integer variable.
IntegerValue LevelZeroLowerBound(IntegerVariable var) const;
IntegerValue LevelZeroUpperBound(IntegerVariable var) const;
// Returns globally valid lower/upper bound on the given affine expression.
IntegerValue LevelZeroLowerBound(AffineExpression exp) const;
IntegerValue LevelZeroUpperBound(AffineExpression exp) const;
// Returns globally valid lower/upper bound on the given linear expression.
IntegerValue LevelZeroLowerBound(LinearExpression2 expr) const;
IntegerValue LevelZeroUpperBound(LinearExpression2 expr) const;
// Returns true if the variable is fixed at level 0.
bool IsFixedAtLevelZero(IntegerVariable var) const;
// Returns true if the affine expression is fixed at level 0.
bool IsFixedAtLevelZero(AffineExpression expr) const;
// Advanced usage.
// Returns the current lower bound assuming the literal is true.
IntegerValue ConditionalLowerBound(Literal l, IntegerVariable i) const;
IntegerValue ConditionalLowerBound(Literal l, AffineExpression expr) const;
// Returns the current upper bound assuming the literal is true.
IntegerValue ConditionalUpperBound(Literal l, IntegerVariable i) const;
IntegerValue ConditionalUpperBound(Literal l, AffineExpression expr) const;
// Advanced usage. Given the reason for
// (Sum_i coeffs[i] * reason[i].var >= current_lb) initially in reason,
// this function relaxes the reason given that we only need the explanation of
// (Sum_i coeffs[i] * reason[i].var >= current_lb - slack).
//
// Preconditions:
// - coeffs must be of same size as reason, and all entry must be positive.
// - *reason must initially contains the trivial initial reason, that is
// the current lower-bound of each variables.
//
// TODO(user): Requiring all initial literal to be at their current bound is
// not really clean. Maybe we can change the API to only take IntegerVariable
// and produce the reason directly.
//
// TODO(user): change API so that this work is performed during the conflict
// analysis where we can be smarter in how we relax the reason. Note however
// that this function is mainly used when we have a conflict, so this is not
// really high priority.
//
// TODO(user): Test that the code work in the presence of integer overflow.
void RelaxLinearReason(IntegerValue slack,
absl::Span<const IntegerValue> coeffs,
std::vector<IntegerLiteral>* reason) const;
// Same as above but take in IntegerVariables instead of IntegerLiterals.
void AppendRelaxedLinearReason(IntegerValue slack,
absl::Span<const IntegerValue> coeffs,
absl::Span<const IntegerVariable> vars,
std::vector<IntegerLiteral>* reason) const;
// Same as above but relax the given trail indices.
void RelaxLinearReason(IntegerValue slack,
absl::Span<const IntegerValue> coeffs,
std::vector<int>* trail_indices) const;
// Removes from the reasons the literal that are always true.
// This is mainly useful for experiments/testing.
void RemoveLevelZeroBounds(std::vector<IntegerLiteral>* reason) const;
// Enqueue new information about a variable bound. Calling this with a less
// restrictive bound than the current one will have no effect.
//
// The reason for this "assignment" must be provided as:
// - A set of Literal currently being all false.
// - A set of IntegerLiteral currently being all true.
//
// IMPORTANT: Notice the inversed sign in the literal reason. This is a bit
// confusing but internally SAT use this direction for efficiency.
//
// Note(user): Duplicates Literal/IntegerLiteral are supported because we call
// STLSortAndRemoveDuplicates() in MergeReasonInto(), but maybe they shouldn't
// for efficiency reason.
//
// TODO(user): If the given bound is equal to the current bound, maybe the new
// reason is better? how to decide and what to do in this case? to think about
// it. Currently we simply don't do anything.
ABSL_MUST_USE_RESULT bool Enqueue(IntegerLiteral i_lit) {
return EnqueueInternal(i_lit, false, {}, {}, integer_trail_.size());
}
ABSL_MUST_USE_RESULT bool Enqueue(
IntegerLiteral i_lit, absl::Span<const Literal> literal_reason,
absl::Span<const IntegerLiteral> integer_reason) {
return EnqueueInternal(i_lit, false, literal_reason, integer_reason,
integer_trail_.size());
}
// Enqueue new information about a variable bound. It has the same behavior
// as the Enqueue() method, except that it accepts true and false integer
// literals, both for i_lit, and for the integer reason.
//
// This method will do nothing if i_lit is a true literal. It will report a
// conflict if i_lit is a false literal, and enqueue i_lit normally otherwise.
// Furthemore, it will check that the integer reason does not contain any
// false literals, and will remove true literals before calling
// ReportConflict() or Enqueue().
ABSL_MUST_USE_RESULT bool SafeEnqueue(
IntegerLiteral i_lit, absl::Span<const IntegerLiteral> integer_reason);
ABSL_MUST_USE_RESULT bool SafeEnqueue(
IntegerLiteral i_lit, absl::Span<const Literal> literal_reason,
absl::Span<const IntegerLiteral> integer_reason);
// Pushes the given integer literal assuming that the Boolean literal is true.
// This can do a few things:
// - If lit it true, add it to the reason and push the integer bound.
// - If the bound is infeasible, push lit to false.
// - If the underlying variable is optional and also controlled by lit, push
// the bound even if lit is not assigned.
ABSL_MUST_USE_RESULT bool ConditionalEnqueue(
Literal lit, IntegerLiteral i_lit, std::vector<Literal>* literal_reason,
std::vector<IntegerLiteral>* integer_reason);
// Same as Enqueue(), but takes an extra argument which if smaller than
// integer_trail_.size() is interpreted as the trail index of an old Enqueue()
// that had the same reason as this one. Note that the given Span must still
// be valid as they are used in case of conflict.
//
// TODO(user): This currently cannot refer to a trail_index with a lazy
// reason. Fix or at least check that this is the case.
ABSL_MUST_USE_RESULT bool Enqueue(
IntegerLiteral i_lit, absl::Span<const Literal> literal_reason,
absl::Span<const IntegerLiteral> integer_reason,
int trail_index_with_same_reason) {
return EnqueueInternal(i_lit, false, literal_reason, integer_reason,
trail_index_with_same_reason);
}
// Lazy reason API.
ABSL_MUST_USE_RESULT bool EnqueueWithLazyReason(
IntegerLiteral i_lit, int id, IntegerValue propagation_slack,
LazyReasonInterface* explainer) {
const int trail_index = integer_trail_.size();
lazy_reasons_.push_back(LazyReasonEntry{explainer, propagation_slack,
i_lit.var, id, trail_index});
return EnqueueInternal(i_lit, true, {}, {}, 0);
}
// Sometimes we infer some root level bounds but we are not at the root level.
// In this case, we will update the level-zero bounds right away, but will
// delay the current push until the next restart.
//
// Note that if you want to also push the literal at the current level, then
// just calling Enqueue() is enough. Since there is no reason, the literal
// will still be recorded properly.
ABSL_MUST_USE_RESULT bool RootLevelEnqueue(IntegerLiteral i_lit);
// Enqueues the given literal on the trail.
// See the comment of Enqueue() for the reason format.
void EnqueueLiteral(Literal literal, absl::Span<const Literal> literal_reason,
absl::Span<const IntegerLiteral> integer_reason);
// Returns the reason (as set of Literal currently false) for a given integer
// literal. Note that the bound must be less restrictive than the current
// bound (checked).
std::vector<Literal> ReasonFor(IntegerLiteral literal) const;
// Appends the reason for the given integer literals to the output and call
// STLSortAndRemoveDuplicates() on it. This function accept "constant"
// literal.
void MergeReasonInto(absl::Span<const IntegerLiteral> literals,
std::vector<Literal>* output) const;
// Returns the number of enqueues that changed a variable bounds. We don't
// count enqueues called with a less restrictive bound than the current one.
//
// Note(user): this can be used to see if any of the bounds changed. Just
// looking at the integer trail index is not enough because at level zero it
// doesn't change since we directly update the "fixed" bounds.
int64_t num_enqueues() const { return num_enqueues_; }
int64_t timestamp() const { return num_enqueues_ + num_untrails_; }
// Same as num_enqueues but only count the level zero changes.
int64_t num_level_zero_enqueues() const { return num_level_zero_enqueues_; }
// All the registered bitsets will be set to one each time a LbVar is
// modified. It is up to the client to clear it if it wants to be notified
// with the newly modified variables.
void RegisterWatcher(SparseBitset<IntegerVariable>* p) {
p->ClearAndResize(NumIntegerVariables());
watchers_.push_back(p);
}
// Helper functions to report a conflict. Always return false so a client can
// simply do: return integer_trail_->ReportConflict(...);
bool ReportConflict(absl::Span<const Literal> literal_reason,
absl::Span<const IntegerLiteral> integer_reason) {
DCHECK(ReasonIsValid(literal_reason, integer_reason));
std::vector<Literal>* conflict = trail_->MutableConflict();
conflict->assign(literal_reason.begin(), literal_reason.end());
MergeReasonInto(integer_reason, conflict);
return false;
}
bool ReportConflict(absl::Span<const IntegerLiteral> integer_reason) {
DCHECK(ReasonIsValid({}, integer_reason));
std::vector<Literal>* conflict = trail_->MutableConflict();
conflict->clear();
MergeReasonInto(integer_reason, conflict);
return false;
}
// Returns true if the variable lower bound is still the one from level zero.
bool VariableLowerBoundIsFromLevelZero(IntegerVariable var) const {
return var_trail_index_[var] < var_lbs_.size();
}
// Registers a reversible class. This class will always be synced with the
// correct decision level.
void RegisterReversibleClass(ReversibleInterface* rev) {
reversible_classes_.push_back(rev);
}
int Index() const { return integer_trail_.size(); }
// Inspects the trail and output all the non-level zero bounds (one per
// variables) to the output. The algo is sparse if there is only a few
// propagations on the trail.
void AppendNewBounds(std::vector<IntegerLiteral>* output) const;
// Inspects the trail and output all the non-level zero bounds from the base
// index (one per variables) to the output. The algo is sparse if there is
// only a few propagations on the trail.
void AppendNewBoundsFrom(int base_index,
std::vector<IntegerLiteral>* output) const;
// Returns the trail index < threshold of a TrailEntry about var. Returns -1
// if there is no such entry (at a positive decision level). This is basically
// the trail index of the lower bound of var at the time.
//
// Important: We do some optimization internally, so this should only be
// used from within a LazyReasonFunction().
int FindTrailIndexOfVarBefore(IntegerVariable var, int threshold) const;
// Basic heuristic to detect when we are in a propagation loop, and suggest
// a good variable to branch on (taking the middle value) to get out of it.
bool InPropagationLoop() const;
void NotifyThatPropagationWasAborted();
IntegerVariable NextVariableToBranchOnInPropagationLoop() const;
// If we had an incomplete propagation, it is important to fix all the
// variables and not really on the propagation to do so. This is related to
// the InPropagationLoop() code above.
bool CurrentBranchHadAnIncompletePropagation();
IntegerVariable FirstUnassignedVariable() const;
// Return true if we can fix new fact at level zero.
bool HasPendingRootLevelDeduction() const {
return !delayed_to_fix_->literal_to_fix.empty() ||
!delayed_to_fix_->integer_literal_to_fix.empty();
}
// If this is set, and in debug mode, we will call this on all conflict to
// be checked for potential issue. Usually against a known optimal solution.
void RegisterDebugChecker(
std::function<bool(absl::Span<const Literal> clause,
absl::Span<const IntegerLiteral> integers)>
checker) {
debug_checker_ = std::move(checker);
}
// This is used by the GreaterThanAtLeastOneOf() lazy reason.
//
// TODO(user): This might better lives together with the propagation code,
// but it does need access to data about the reason/conflict being currently
// computed. Also for speed we do need all the code here in on block. Given
// than we have just a few "lazy integer reason", we might not really want a
// generic code in any case.
void AddAllGreaterThanConstantReason(absl::Span<AffineExpression> exprs,
IntegerValue target_min,
std::vector<int>* indices) const {
constexpr int64_t check_period = 1e6;
int64_t limit_check = work_done_in_explain_lower_than_ + check_period;
for (const AffineExpression& expr : exprs) {
if (expr.IsConstant()) {
DCHECK_GE(expr.constant, target_min);
continue;
}
DCHECK_NE(expr.var, kNoIntegerVariable);
const IntegerLiteral to_explain = expr.GreaterOrEqual(target_min);
if (IsTrueAtLevelZero(to_explain)) continue;
// On large routing problems, we can spend a lot of time in this loop.
if (work_done_in_explain_lower_than_ > limit_check) {
limit_check = work_done_in_explain_lower_than_ + check_period;
if (time_limit_->LimitReached()) return;
}
// Skip if we already have an explanation for expr >= target_min. Note
// that we already do that while processing the returned indices, so this
// mainly save a FindLowestTrailIndexThatExplainBound() call per skipped
// indices, which can still be costly.
{
const int index = tmp_var_to_trail_index_in_queue_[to_explain.var];
if (index == std::numeric_limits<int>::max()) continue;
if (index > 0 && integer_trail_[index].bound >= to_explain.bound) {
has_dependency_ = true;
continue;
}
}
// We need to find the index that explain the bound.
indices->push_back(FindLowestTrailIndexThatExplainBound(to_explain));
}
}
private:
// Used for DHECKs to validate the reason given to the public functions above.
// Tests that all Literal are false. Tests that all IntegerLiteral are true.
bool ReasonIsValid(absl::Span<const Literal> literal_reason,
absl::Span<const IntegerLiteral> integer_reason);
// Same as above, but with the literal for which this is the reason for.
bool ReasonIsValid(Literal lit, absl::Span<const Literal> literal_reason,
absl::Span<const IntegerLiteral> integer_reason);
bool ReasonIsValid(IntegerLiteral i_lit,
absl::Span<const Literal> literal_reason,
absl::Span<const IntegerLiteral> integer_reason);
// If the variable has holes in its domain, make sure the literal is
// canonicalized.
void CanonicalizeLiteralIfNeeded(IntegerLiteral* i_lit);
// Called by the Enqueue() functions that detected a conflict. This does some
// common conflict initialization that must terminate by a call to
// MergeReasonIntoInternal(conflict) where conflict is the returned vector.
std::vector<Literal>* InitializeConflict(
IntegerLiteral integer_literal, bool use_lazy_reason,
absl::Span<const Literal> literals_reason,
absl::Span<const IntegerLiteral> bounds_reason);
// Saves the given reason and return its index.
int AppendReasonToInternalBuffers(
absl::Span<const Literal> literal_reason,
absl::Span<const IntegerLiteral> integer_reason);
// Internal implementation of the different public Enqueue() functions.
ABSL_MUST_USE_RESULT bool EnqueueInternal(
IntegerLiteral i_lit, bool use_lazy_reason,
absl::Span<const Literal> literal_reason,
absl::Span<const IntegerLiteral> integer_reason,
int trail_index_with_same_reason);
// Internal implementation of the EnqueueLiteral() functions.
void EnqueueLiteralInternal(Literal literal, bool use_lazy_reason,
absl::Span<const Literal> literal_reason,
absl::Span<const IntegerLiteral> integer_reason);
// Same as EnqueueInternal() but for the case where we push an IntegerLiteral
// because an associated Literal is true (and we know it). In this case, we
// have less work to do, so this has the same effect but is faster.
ABSL_MUST_USE_RESULT bool EnqueueAssociatedIntegerLiteral(
IntegerLiteral i_lit, Literal literal_reason);
// Does the work of MergeReasonInto() when queue_ is already initialized.
void MergeReasonIntoInternal(std::vector<Literal>* output,
int64_t conflict_id) const;
// Returns the lowest trail index of a TrailEntry that can be used to explain
// the given IntegerLiteral. The literal must be currently true but not true
// at level zero (DCHECKed).
int FindLowestTrailIndexThatExplainBound(IntegerLiteral i_lit) const;
// This must be called before Dependencies() or AppendLiteralsReason().
//
// TODO(user): Not really robust, try to find a better way.
void ComputeLazyReasonIfNeeded(int reason_index) const;
// Helper function to return the "dependencies" of a bound assignment.
// All the TrailEntry at these indices are part of the reason for this
// assignment.
//
// Important: The returned Span is only valid up to the next call.
absl::Span<const int> Dependencies(int reason_index) const;
// Helper function to append the Literal part of the reason for this bound
// assignment. We use added_variables_ to not add the same literal twice.
// Note that looking at literal.Variable() is enough since all the literals
// of a reason must be false.
void AppendLiteralsReason(int reason_index,
std::vector<Literal>* output) const;
// Returns some debugging info.
std::string DebugString();
// Used internally to return the next conflict number.
int64_t NextConflictId();
// Information for each integer variable about its current lower bound and
// position of the last TrailEntry in the trail referring to this var.
util_intops::StrongVector<IntegerVariable, IntegerValue> var_lbs_;
util_intops::StrongVector<IntegerVariable, int> var_trail_index_;
// This is used by FindLowestTrailIndexThatExplainBound() and
// FindTrailIndexOfVarBefore() to speed up the lookup. It keeps a trail index
// for each variable that may or may not point to a TrailEntry regarding this
// variable. The validity of the index is verified before being used.
//
// The cache will only be updated with trail_index >= threshold.
mutable int var_trail_index_cache_threshold_ = 0;
mutable util_intops::StrongVector<IntegerVariable, int>
var_trail_index_cache_;
// Used by GetOrCreateConstantIntegerVariable() to return already created
// constant variables that share the same value.
absl::flat_hash_map<IntegerValue, IntegerVariable> constant_map_;
// The integer trail. It always start by num_vars sentinel values with the
// level 0 bounds (in one to one correspondence with var_lbs_).
struct TrailEntry {
IntegerValue bound;
IntegerVariable var;
int32_t prev_trail_index;
// Index in literals_reason_start_/bounds_reason_starts_ If this is negative
// then it is a lazy reason.
int32_t reason_index;
};
std::vector<TrailEntry> integer_trail_;
struct LazyReasonEntry {
LazyReasonInterface* explainer;
IntegerValue propagation_slack;
IntegerVariable var_to_explain;
int id;
int trail_index_at_propagation_time;
void Explain(std::vector<Literal>* literals,
std::vector<int>* dependencies) const {
explainer->Explain(id, propagation_slack, var_to_explain,
trail_index_at_propagation_time, literals,
dependencies);
}
};
std::vector<int> lazy_reason_decision_levels_;
std::vector<LazyReasonEntry> lazy_reasons_;
// Start of each decision levels in integer_trail_.
// TODO(user): use more general reversible mechanism?
std::vector<int> integer_search_levels_;
// Buffer to store the reason of each trail entry.
std::vector<int> reason_decision_levels_;
std::vector<int> literals_reason_starts_;
std::vector<Literal> literals_reason_buffer_;
// The last two vectors are in one to one correspondence. Dependencies() will
// "cache" the result of the conversion from IntegerLiteral to trail indices
// in trail_index_reason_buffer_.
std::vector<int> bounds_reason_starts_;
mutable std::vector<int> cached_sizes_;
std::vector<IntegerLiteral> bounds_reason_buffer_;
mutable std::vector<int> trail_index_reason_buffer_;
// Temporary vector filled by calls to LazyReasonFunction().
mutable std::vector<Literal> lazy_reason_literals_;
mutable std::vector<int> lazy_reason_trail_indices_;
// Temporary data used by MergeReasonInto().
mutable bool has_dependency_ = false;
mutable std::vector<int> tmp_queue_;
mutable std::vector<IntegerVariable> tmp_to_clear_;
mutable util_intops::StrongVector<IntegerVariable, int>
tmp_var_to_trail_index_in_queue_;
mutable SparseBitset<BooleanVariable> added_variables_;
// Temporary heap used by RelaxLinearReason();
struct RelaxHeapEntry {
int index;
IntegerValue coeff;
int64_t diff;
bool operator<(const RelaxHeapEntry& o) const { return index < o.index; }
};
mutable std::vector<RelaxHeapEntry> relax_heap_;
mutable std::vector<int> tmp_indices_;
// Temporary data used by AppendNewBounds().
mutable SparseBitset<IntegerVariable> tmp_marked_;
// Temporary data used by SafeEnqueue();
std::vector<IntegerLiteral> tmp_cleaned_reason_;
// For EnqueueLiteral(), we store the reason index at its Boolean trail index.
std::vector<int> boolean_trail_index_to_reason_index_;
// We need to know if we skipped some propagation in the current branch.
// This is reverted as we backtrack over it.
int first_level_without_full_propagation_ = -1;
// This is used to detect when MergeReasonIntoInternal() is called multiple
// time while processing the same conflict. It allows to optimize the reason
// and the time taken to compute it.
mutable int64_t last_conflict_id_ = -1;
mutable bool info_is_valid_on_subsequent_last_level_expansion_ = false;
mutable util_intops::StrongVector<IntegerVariable, int>
var_to_trail_index_at_lower_level_;
mutable std::vector<int> tmp_seen_;
mutable std::vector<IntegerVariable> to_clear_for_lower_level_;
int64_t num_enqueues_ = 0;
int64_t num_untrails_ = 0;
int64_t num_level_zero_enqueues_ = 0;
mutable int64_t num_decisions_to_break_loop_ = 0;
std::vector<SparseBitset<IntegerVariable>*> watchers_;
std::vector<ReversibleInterface*> reversible_classes_;
mutable int64_t work_done_in_explain_lower_than_ = 0;
mutable Domain temp_domain_;
DelayedRootLevelDeduction* delayed_to_fix_;
IntegerDomains* domains_;
IntegerEncoder* encoder_;
Trail* trail_;
SatSolver* sat_solver_;
TimeLimit* time_limit_;
const SatParameters& parameters_;
// Temporary "hash" to keep track of all the conditional enqueue that were
// done. Note that we currently do not keep any reason for them, and as such,
// we can only use this in heuristics. See ConditionalLowerBound().
absl::flat_hash_map<std::pair<LiteralIndex, IntegerVariable>, IntegerValue>
conditional_lbs_;
std::function<bool(absl::Span<const Literal> clause,
absl::Span<const IntegerLiteral> integers)>
debug_checker_ = nullptr;
};
// Base class for CP like propagators.
class PropagatorInterface {
public:
PropagatorInterface() = default;
virtual ~PropagatorInterface() = default;
// This will be called after one or more literals that are watched by this
// propagator changed. It will also always be called on the first propagation
// cycle after registration.
virtual bool Propagate() = 0;
// This will only be called on a non-empty vector, otherwise Propagate() will
// be called. The passed vector will contain the "watch index" of all the
// literals that were given one at registration and that changed since the
// last call to Propagate(). This is only true when going down in the search
// tree, on backjump this list will be cleared.
//
// Notes:
// - The indices may contain duplicates if the same integer variable as been
// updated many times or if different watched literals have the same
// watch_index.
// - At level zero, it will not contain any indices associated with literals
// that were already fixed when the propagator was registered. Only the
// indices of the literals modified after the registration will be present.
virtual bool IncrementalPropagate(const std::vector<int>& /*watch_indices*/) {
LOG(FATAL) << "Not implemented.";
return false; // Remove warning in Windows
}
};
// Singleton for basic reversible types. We need the wrapper so that they can be
// accessed with model->GetOrCreate<>() and properly registered at creation.
class RevIntRepository : public RevRepository<int> {
public:
explicit RevIntRepository(Model* model) {
model->GetOrCreate<IntegerTrail>()->RegisterReversibleClass(this);
}
};
class RevIntegerValueRepository : public RevRepository<IntegerValue> {
public:
explicit RevIntegerValueRepository(Model* model) {
model->GetOrCreate<IntegerTrail>()->RegisterReversibleClass(this);
}
};
// This class allows registering Propagator that will be called if a
// watched Literal or LbVar changes.
//
// TODO(user): Move this to its own file. Add unit tests!
class GenericLiteralWatcher final : public SatPropagator {
public:
explicit GenericLiteralWatcher(Model* model);
// This type is neither copyable nor movable.
GenericLiteralWatcher(const GenericLiteralWatcher&) = delete;
GenericLiteralWatcher& operator=(const GenericLiteralWatcher&) = delete;
~GenericLiteralWatcher() final = default;
// Memory optimization: you can call this before registering watchers.
void ReserveSpaceForNumVariables(int num_vars);
// On propagate, the registered propagators will be called if they need to
// until a fixed point is reached. Propagators with low ids will tend to be
// called first, but it ultimately depends on their "waking" order.
bool Propagate(Trail* trail) final;
void Untrail(const Trail& trail, int literal_trail_index) final;
// Registers a propagator and returns its unique ids.
int Register(PropagatorInterface* propagator);
// Changes the priority of the propagator with given id. The priority is a
// non-negative integer. Propagators with a lower priority will always be
// run before the ones with a higher one. The default priority is one.
void SetPropagatorPriority(int id, int priority);
// The default behavior is to assume that a propagator does not need to be
// called twice in a row. However, propagators on which this is called will be
// called again if they change one of their own watched variables.
void NotifyThatPropagatorMayNotReachFixedPointInOnePass(int id);
// Whether we call a propagator even if its watched variables didn't change.
// This is only used when we are back to level zero. This was introduced for
// the LP propagator where we might need to continue an interrupted solve or
// add extra cuts at level zero.
void AlwaysCallAtLevelZero(int id);
// Watches the corresponding quantity. The propagator with given id will be
// called if it changes. Note that WatchLiteral() only trigger when the
// literal becomes true.
//
// If watch_index is specified, it is associated with the watched literal.
// Doing this will cause IncrementalPropagate() to be called (see the
// documentation of this interface for more detail).
void WatchLiteral(Literal l, int id, int watch_index = -1);
void WatchLowerBound(IntegerVariable var, int id, int watch_index = -1);
void WatchUpperBound(IntegerVariable var, int id, int watch_index = -1);
void WatchIntegerVariable(IntegerVariable i, int id, int watch_index = -1);
// Because the coeff is always positive, watching an affine expression is
// the same as watching its var.
void WatchLowerBound(AffineExpression e, int id) {
WatchLowerBound(e.var, id);
}
void WatchUpperBound(AffineExpression e, int id) {
WatchUpperBound(e.var, id);
}
void WatchAffineExpression(AffineExpression e, int id) {
WatchIntegerVariable(e.var, id);
}
// No-op overload for "constant" IntegerVariable that are sometimes templated
// as an IntegerValue.
void WatchLowerBound(IntegerValue /*i*/, int /*id*/) {}
void WatchUpperBound(IntegerValue /*i*/, int /*id*/) {}
void WatchIntegerVariable(IntegerValue /*v*/, int /*id*/) {}
// Registers a reversible class with a given propagator. This class will be
// changed to the correct state just before the propagator is called.
//
// Doing it just before should minimize cache-misses and bundle as much as
// possible the "backtracking" together. Many propagators only watches a
// few variables and will not be called at each decision levels.
void RegisterReversibleClass(int id, ReversibleInterface* rev);
// Registers a reversible int with a given propagator. The int will be changed
// to its correct value just before Propagate() is called.
//
// Note that this will work in O(num_rev_int_of_propagator_id) per call to
// Propagate() and happens at most once per decision level. As such this is
// meant for classes that have just a few reversible ints or that will have a
// similar complexity anyway.
//
// Alternatively, one can directly get the underlying RevRepository<int> with
// a call to model.Get<>(), and use SaveWithStamp() before each modification
// to have just a slight overhead per int updates. This later option is what
// is usually done in a CP solver at the cost of a slightly more complex API.
void RegisterReversibleInt(int id, int* rev);
// A simple form of incremental update is to maintain state as we dive into
// the search tree but forget everything on every backtrack. A propagator
// can be called many times by decision, so this can make a large proportion
// of the calls incremental.
//
// This allows to achieve this with a really low overhead.
//
// The propagator can define a bool rev_is_in_dive_ = false; and at the
// beginning of each propagate do:
// const bool no_backtrack_since_last_call = rev_is_in_dive_;
// watcher_->SetUntilNextBacktrack(&rev_is_in_dive_);
void SetUntilNextBacktrack(bool* is_in_dive) {
if (!*is_in_dive) {
*is_in_dive = true;
bool_to_reset_on_backtrack_.push_back(is_in_dive);
}
}
// Returns the number of registered propagators.
int NumPropagators() const { return in_queue_.size(); }
// Set a callback for new variable bounds at level 0.
//
// This will be called (only at level zero) with the list of IntegerVariable
// with changed lower bounds. Note that it might be called more than once
// during the same propagation cycle if we fix variables in "stages".
//
// Also note that this will be called if some BooleanVariable where fixed even
// if no IntegerVariable are changed, so the passed vector to the function
// might be empty.
void RegisterLevelZeroModifiedVariablesCallback(
const std::function<void(const std::vector<IntegerVariable>&)> cb) {
level_zero_modified_variable_callback_.push_back(cb);
}
// This will be called not too often during propagation (when we finish
// propagating one priority). If it returns true, we will stop propagation
// there. It is used by LbTreeSearch as we can stop as soon as the objective
// lower bound crossed a threshold and do not need to call expensive
// propagator when this is the case.
void SetStopPropagationCallback(std::function<bool()> callback) {
stop_propagation_callback_ = callback;
}
// Returns the id of the propagator we are currently calling. This is meant
// to be used from inside Propagate() in case a propagator was registered
// more than once at different priority for instance.
int GetCurrentId() const { return current_id_; }
// Add the given propagator to its queue.
//
// Warning: This will have no effect if called from within the propagation of
// a propagator since the propagator is still marked as "in the queue" until
// its propagation is done. Use CallAgainDuringThisPropagation() if that is
// what you need instead.
void CallOnNextPropagate(int id);
void CallAgainDuringThisPropagation() { call_again_ = true; };
private:
// Updates queue_ and in_queue_ with the propagator ids that need to be
// called.
void UpdateCallingNeeds(Trail* trail);
TimeLimit* time_limit_;
IntegerTrail* integer_trail_;
RevIntRepository* rev_int_repository_;
struct WatchData {
int id;
int watch_index;
bool operator==(const WatchData& o) const {
return id == o.id && watch_index == o.watch_index;
}
};
util_intops::StrongVector<LiteralIndex, std::vector<WatchData>>
literal_to_watcher_;
util_intops::StrongVector<IntegerVariable, std::vector<WatchData>>
var_to_watcher_;
std::vector<PropagatorInterface*> watchers_;
SparseBitset<IntegerVariable> modified_vars_;
// For RegisterLevelZeroModifiedVariablesCallback().
SparseBitset<IntegerVariable> modified_vars_for_callback_;
// Propagator ids that needs to be called. There is one queue per priority but
// just one Boolean to indicate if a propagator is in one of them.
std::vector<std::deque<int>> queue_by_priority_;
std::vector<bool> in_queue_;
// Data for each propagator.
DEFINE_STRONG_INDEX_TYPE(IdType);
std::vector<bool> id_need_reversible_support_;
std::vector<int> id_to_level_at_last_call_;
RevVector<IdType, int> id_to_greatest_common_level_since_last_call_;
std::vector<std::vector<ReversibleInterface*>> id_to_reversible_classes_;
std::vector<std::vector<int*>> id_to_reversible_ints_;
std::vector<std::vector<int>> id_to_watch_indices_;
std::vector<int> id_to_priority_;
std::vector<int> id_to_idempotence_;
// Special propagators that needs to always be called at level zero.
std::vector<int> propagator_ids_to_call_at_level_zero_;
// The id of the propagator we just called.
int current_id_;
bool call_again_ = false;
std::vector<std::function<void(const std::vector<IntegerVariable>&)>>
level_zero_modified_variable_callback_;
std::function<bool()> stop_propagation_callback_;
std::vector<bool*> bool_to_reset_on_backtrack_;
};
// ============================================================================
// Implementation.
// ============================================================================
inline IntegerValue IntegerTrail::LowerBound(IntegerVariable i) const {
return var_lbs_[i];
}
inline IntegerValue IntegerTrail::UpperBound(IntegerVariable i) const {
return -var_lbs_[NegationOf(i)];
}
inline bool IntegerTrail::IsFixed(IntegerVariable i) const {
return var_lbs_[i] == -var_lbs_[NegationOf(i)];
}
inline IntegerValue IntegerTrail::FixedValue(IntegerVariable i) const {
DCHECK(IsFixed(i));
return var_lbs_[i];
}
inline IntegerValue IntegerTrail::ConditionalLowerBound(
Literal l, IntegerVariable i) const {
const auto it = conditional_lbs_.find({l.Index(), i});
if (it != conditional_lbs_.end()) {
return std::max(var_lbs_[i], it->second);
}
return var_lbs_[i];
}
inline IntegerValue IntegerTrail::ConditionalLowerBound(
Literal l, AffineExpression expr) const {
if (expr.var == kNoIntegerVariable) return expr.constant;
return ConditionalLowerBound(l, expr.var) * expr.coeff + expr.constant;
}
inline IntegerValue IntegerTrail::ConditionalUpperBound(
Literal l, IntegerVariable i) const {
return -ConditionalLowerBound(l, NegationOf(i));
}
inline IntegerValue IntegerTrail::ConditionalUpperBound(
Literal l, AffineExpression expr) const {
if (expr.var == kNoIntegerVariable) return expr.constant;
return ConditionalUpperBound(l, expr.var) * expr.coeff + expr.constant;
}
inline IntegerLiteral IntegerTrail::LowerBoundAsLiteral(
IntegerVariable i) const {
return IntegerLiteral::GreaterOrEqual(i, LowerBound(i));
}
inline IntegerLiteral IntegerTrail::UpperBoundAsLiteral(
IntegerVariable i) const {
return IntegerLiteral::LowerOrEqual(i, UpperBound(i));
}
inline IntegerValue IntegerTrail::LowerBound(AffineExpression expr) const {
if (expr.var == kNoIntegerVariable) return expr.constant;
return LowerBound(expr.var) * expr.coeff + expr.constant;
}
inline IntegerValue IntegerTrail::UpperBound(AffineExpression expr) const {
if (expr.var == kNoIntegerVariable) return expr.constant;
return UpperBound(expr.var) * expr.coeff + expr.constant;
}
inline IntegerValue IntegerTrail::UpperBound(LinearExpression2 expr) const {
IntegerValue result = 0;
for (int i = 0; i < 2; ++i) {
if (expr.coeffs[i] == 0) {
continue;
} else if (expr.coeffs[i] > 0) {
result += expr.coeffs[i] * UpperBound(expr.vars[i]);
} else {
result += expr.coeffs[i] * LowerBound(expr.vars[i]);
}
}
return result;
}
inline bool IntegerTrail::IsFixed(AffineExpression expr) const {
if (expr.var == kNoIntegerVariable) return true;
return IsFixed(expr.var);
}
inline IntegerValue IntegerTrail::FixedValue(AffineExpression expr) const {
if (expr.var == kNoIntegerVariable) return expr.constant;
return FixedValue(expr.var) * expr.coeff + expr.constant;
}
inline IntegerLiteral IntegerTrail::LowerBoundAsLiteral(
AffineExpression expr) const {
if (expr.var == kNoIntegerVariable) return IntegerLiteral::TrueLiteral();
return IntegerLiteral::GreaterOrEqual(expr.var, LowerBound(expr.var));
}
inline IntegerLiteral IntegerTrail::UpperBoundAsLiteral(
AffineExpression expr) const {
if (expr.var == kNoIntegerVariable) return IntegerLiteral::TrueLiteral();
return IntegerLiteral::LowerOrEqual(expr.var, UpperBound(expr.var));
}
inline bool IntegerTrail::IntegerLiteralIsTrue(IntegerLiteral l) const {
return l.bound <= LowerBound(l.var);
}
inline bool IntegerTrail::IntegerLiteralIsFalse(IntegerLiteral l) const {
return l.bound > UpperBound(l.var);
}
inline bool IntegerTrail::IsTrueAtLevelZero(IntegerLiteral l) const {
return l.bound <= LevelZeroLowerBound(l.var);
}
// The level zero bounds are stored at the beginning of the trail and they also
// serves as sentinels. Their index match the variables index.
inline IntegerValue IntegerTrail::LevelZeroLowerBound(
IntegerVariable var) const {
DCHECK_GE(var, 0);
DCHECK_LT(var, integer_trail_.size());
return integer_trail_[var.value()].bound;
}
inline IntegerValue IntegerTrail::LevelZeroUpperBound(
IntegerVariable var) const {
return -integer_trail_[NegationOf(var).value()].bound;
}
inline bool IntegerTrail::IsFixedAtLevelZero(IntegerVariable var) const {
return integer_trail_[var.value()].bound ==
-integer_trail_[NegationOf(var).value()].bound;
}
inline IntegerValue IntegerTrail::LevelZeroLowerBound(
AffineExpression expr) const {
if (expr.var == kNoIntegerVariable) return expr.constant;
return expr.ValueAt(LevelZeroLowerBound(expr.var));
}
inline IntegerValue IntegerTrail::LevelZeroUpperBound(
AffineExpression expr) const {
if (expr.var == kNoIntegerVariable) return expr.constant;
return expr.ValueAt(LevelZeroUpperBound(expr.var));
}
inline IntegerValue IntegerTrail::LevelZeroLowerBound(
LinearExpression2 expr) const {
expr.SimpleCanonicalization();
IntegerValue result = 0;
for (int i = 0; i < 2; ++i) {
if (expr.coeffs[i] != 0) {
result += expr.coeffs[i] * LevelZeroLowerBound(expr.vars[i]);
}
}
return result;
}
inline IntegerValue IntegerTrail::LevelZeroUpperBound(
LinearExpression2 expr) const {
expr.SimpleCanonicalization();
IntegerValue result = 0;
for (int i = 0; i < 2; ++i) {
if (expr.coeffs[i] != 0) {
result += expr.coeffs[i] * LevelZeroUpperBound(expr.vars[i]);
}
}
return result;
}
inline bool IntegerTrail::IsFixedAtLevelZero(AffineExpression expr) const {
if (expr.var == kNoIntegerVariable) return true;
return IsFixedAtLevelZero(expr.var);
}
inline void GenericLiteralWatcher::WatchLiteral(Literal l, int id,
int watch_index) {
if (l.Index() >= literal_to_watcher_.size()) {
literal_to_watcher_.resize(l.Index().value() + 1);
}
literal_to_watcher_[l].push_back({id, watch_index});
}
inline void GenericLiteralWatcher::WatchLowerBound(IntegerVariable var, int id,
int watch_index) {
if (var == kNoIntegerVariable) return;
if (var.value() >= var_to_watcher_.size()) {
var_to_watcher_.resize(var.value() + 1);
}
// Minor optim, so that we don't watch the same variable twice. Propagator
// code is easier this way since for example when one wants to watch both
// an interval start and interval end, both might have the same underlying
// variable.
const WatchData data = {id, watch_index};
if (!var_to_watcher_[var].empty() && var_to_watcher_[var].back() == data) {
return;
}
var_to_watcher_[var].push_back(data);
}
inline void GenericLiteralWatcher::WatchUpperBound(IntegerVariable var, int id,
int watch_index) {
if (var == kNoIntegerVariable) return;
WatchLowerBound(NegationOf(var), id, watch_index);
}
inline void GenericLiteralWatcher::WatchIntegerVariable(IntegerVariable i,
int id,
int watch_index) {
WatchLowerBound(i, id, watch_index);
WatchUpperBound(i, id, watch_index);
}
// ============================================================================
// Model based functions.
//
// Note that in the model API, we simply use int64_t for the integer values, so
// that it is nicer for the client. Internally these are converted to
// IntegerValue which is typechecked.
// ============================================================================
inline std::function<BooleanVariable(Model*)> NewBooleanVariable() {
return [=](Model* model) {
return model->GetOrCreate<SatSolver>()->NewBooleanVariable();
};
}
inline std::function<IntegerVariable(Model*)> ConstantIntegerVariable(
int64_t value) {
return [=](Model* model) {
return model->GetOrCreate<IntegerTrail>()
->GetOrCreateConstantIntegerVariable(IntegerValue(value));
};
}
inline std::function<IntegerVariable(Model*)> NewIntegerVariable(int64_t lb,
int64_t ub) {
return [=](Model* model) {
CHECK_LE(lb, ub);
return model->GetOrCreate<IntegerTrail>()->AddIntegerVariable(
IntegerValue(lb), IntegerValue(ub));
};
}
inline std::function<IntegerVariable(Model*)> NewIntegerVariable(
const Domain& domain) {
return [=](Model* model) {
return model->GetOrCreate<IntegerTrail>()->AddIntegerVariable(domain);
};
}
// Creates a 0-1 integer variable "view" of the given literal. It will have a
// value of 1 when the literal is true, and 0 when the literal is false.
inline IntegerVariable CreateNewIntegerVariableFromLiteral(Literal lit,
Model* model) {
auto* encoder = model->GetOrCreate<IntegerEncoder>();
const IntegerVariable candidate = encoder->GetLiteralView(lit);
if (candidate != kNoIntegerVariable) return candidate;
IntegerVariable var;
auto* integer_trail = model->GetOrCreate<IntegerTrail>();
const auto& assignment = model->GetOrCreate<SatSolver>()->Assignment();
if (assignment.LiteralIsTrue(lit)) {
var = integer_trail->GetOrCreateConstantIntegerVariable(IntegerValue(1));
} else if (assignment.LiteralIsFalse(lit)) {
var = integer_trail->GetOrCreateConstantIntegerVariable(IntegerValue(0));
} else {
var = integer_trail->AddIntegerVariable(IntegerValue(0), IntegerValue(1));
}
encoder->AssociateToIntegerEqualValue(lit, var, IntegerValue(1));
DCHECK_NE(encoder->GetLiteralView(lit), kNoIntegerVariable);
return var;
}
// Deprecated.
inline std::function<IntegerVariable(Model*)> NewIntegerVariableFromLiteral(
Literal lit) {
return [=](Model* model) {
return CreateNewIntegerVariableFromLiteral(lit, model);
};
}
inline std::function<int64_t(const Model&)> LowerBound(IntegerVariable v) {
return [=](const Model& model) {
return model.Get<IntegerTrail>()->LowerBound(v).value();
};
}
inline std::function<int64_t(const Model&)> UpperBound(IntegerVariable v) {
return [=](const Model& model) {
return model.Get<IntegerTrail>()->UpperBound(v).value();
};
}
inline std::function<bool(const Model&)> IsFixed(IntegerVariable v) {
return [=](const Model& model) {
const IntegerTrail* trail = model.Get<IntegerTrail>();
return trail->LowerBound(v) == trail->UpperBound(v);
};
}
// This checks that the variable is fixed.
inline std::function<int64_t(const Model&)> Value(IntegerVariable v) {
return [=](const Model& model) {
const IntegerTrail* trail = model.Get<IntegerTrail>();
CHECK_EQ(trail->LowerBound(v), trail->UpperBound(v)) << v;
return trail->LowerBound(v).value();
};
}
inline std::function<void(Model*)> GreaterOrEqual(IntegerVariable v,
int64_t lb) {
return [=](Model* model) {
if (!model->GetOrCreate<IntegerTrail>()->Enqueue(
IntegerLiteral::GreaterOrEqual(v, IntegerValue(lb)),
std::vector<Literal>(), std::vector<IntegerLiteral>())) {
model->GetOrCreate<SatSolver>()->NotifyThatModelIsUnsat();
VLOG(1) << "Model trivially infeasible, variable " << v
<< " has upper bound " << model->Get(UpperBound(v))
<< " and GreaterOrEqual() was called with a lower bound of "
<< lb;
}
};
}
inline std::function<void(Model*)> LowerOrEqual(IntegerVariable v, int64_t ub) {
return [=](Model* model) {
if (!model->GetOrCreate<IntegerTrail>()->Enqueue(
IntegerLiteral::LowerOrEqual(v, IntegerValue(ub)),
std::vector<Literal>(), std::vector<IntegerLiteral>())) {
model->GetOrCreate<SatSolver>()->NotifyThatModelIsUnsat();
VLOG(1) << "Model trivially infeasible, variable " << v
<< " has lower bound " << model->Get(LowerBound(v))
<< " and LowerOrEqual() was called with an upper bound of " << ub;
}
};
}
// Fix v to a given value.
inline std::function<void(Model*)> Equality(IntegerVariable v, int64_t value) {
return [=](Model* model) {
model->Add(LowerOrEqual(v, value));
model->Add(GreaterOrEqual(v, value));
};
}
// TODO(user): This is one of the rare case where it is better to use Equality()
// rather than two Implications(). Maybe we should modify our internal
// implementation to use half-reified encoding? that is do not propagate the
// direction integer-bound => literal, but just literal => integer-bound? This
// is the same as using different underlying variable for an integer literal and
// its negation.
inline std::function<void(Model*)> Implication(
absl::Span<const Literal> enforcement_literals, IntegerLiteral i) {
return [=](Model* model) {
auto* sat_solver = model->GetOrCreate<SatSolver>();
auto* integer_trail = model->GetOrCreate<IntegerTrail>();
if (i.bound <= integer_trail->LowerBound(i.var)) {
// Always true! nothing to do.
} else if (i.bound > integer_trail->UpperBound(i.var)) {
// Always false.
std::vector<Literal> clause;
for (const Literal literal : enforcement_literals) {
clause.push_back(literal.Negated());
}
sat_solver->AddClauseDuringSearch(clause);
} else {
// TODO(user): Double check what happen when we associate a trivially
// true or false literal.
IntegerEncoder* encoder = model->GetOrCreate<IntegerEncoder>();
std::vector<Literal> clause{encoder->GetOrCreateAssociatedLiteral(i)};
for (const Literal literal : enforcement_literals) {
clause.push_back(literal.Negated());
}
sat_solver->AddClauseDuringSearch(clause);
}
};
}
// in_interval => v in [lb, ub].
inline std::function<void(Model*)> ImpliesInInterval(Literal in_interval,
IntegerVariable v,
int64_t lb, int64_t ub) {
return [=](Model* model) {
if (lb == ub) {
IntegerEncoder* encoder = model->GetOrCreate<IntegerEncoder>();
model->Add(Implication({in_interval},
encoder->GetOrCreateLiteralAssociatedToEquality(
v, IntegerValue(lb))));
return;
}
model->Add(Implication(
{in_interval}, IntegerLiteral::GreaterOrEqual(v, IntegerValue(lb))));
model->Add(Implication({in_interval},
IntegerLiteral::LowerOrEqual(v, IntegerValue(ub))));
};
}
// Calling model.Add(FullyEncodeVariable(var)) will create one literal per value
// in the domain of var (if not already done), and wire everything correctly.
// This also returns the full encoding, see the FullDomainEncoding() method of
// the IntegerEncoder class.
inline std::function<std::vector<ValueLiteralPair>(Model*)> FullyEncodeVariable(
IntegerVariable var) {
return [=](Model* model) {
IntegerEncoder* encoder = model->GetOrCreate<IntegerEncoder>();
if (!encoder->VariableIsFullyEncoded(var)) {
encoder->FullyEncodeVariable(var);
}
return encoder->FullDomainEncoding(var);
};
}
} // namespace sat
} // namespace operations_research
#endif // OR_TOOLS_SAT_INTEGER_H_