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ortools-clone/ortools/sat/sat_inprocessing.h

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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.
// This file contains the entry point for our presolve/inprocessing code.
//
// TODO(user): for now it is mainly presolve, but the idea is to call these
// function during the search so they should be as incremental as possible. That
// is avoid doing work that is not useful because nothing changed or exploring
// parts that were not done during the last round.
#ifndef OR_TOOLS_SAT_SAT_INPROCESSING_H_
#define OR_TOOLS_SAT_SAT_INPROCESSING_H_
#include "ortools/sat/clause.h"
#include "ortools/sat/model.h"
#include "ortools/sat/sat_base.h"
#include "ortools/sat/sat_solver.h"
#include "ortools/sat/util.h"
#include "ortools/util/time_limit.h"
namespace operations_research {
namespace sat {
class StampingSimplifier;
struct SatPresolveOptions {
// The time budget to spend.
double deterministic_time_limit = 30.0;
// We assume this is also true if --v 1 is activated and we actually log
// even more in --v 1.
bool log_info = false;
// See ProbingOptions in probing.h
bool extract_binary_clauses_in_probing = false;
// Whether we perform a transitive reduction of the binary implication graph
// after equivalent literal detection and before each probing pass.
//
// TODO(user): Doing that before the current SAT presolve also change the
// possible reduction. This shouldn't matter if we use the binary implication
// graph and its reachability instead of just binary clause though.
bool use_transitive_reduction = false;
};
// We need to keep some information from one call to the next, so we use a
// class. Note that as this becomes big, we can probably split it.
//
// TODO(user): Some algorithms here use the normal SAT propagation engine.
// However we might want to temporarily disable activities/phase saving and so
// on if we want to run them as in-processing steps so that they
// do not "pollute" the normal SAT search.
//
// TODO(user): For the propagation, this depends on the SatSolver class, which
// mean we cannot really use it without some refactoring as an in-processing
// from the SatSolver::Solve() function. So we do need a special
// InprocessingSolve() that lives outside SatSolver. Alternatively, we can
// extract the propagation main loop and conflict analysis from SatSolver.
class Inprocessing {
public:
explicit Inprocessing(Model* model)
: assignment_(model->GetOrCreate<Trail>()->Assignment()),
implication_graph_(model->GetOrCreate<BinaryImplicationGraph>()),
clause_manager_(model->GetOrCreate<LiteralWatchers>()),
trail_(model->GetOrCreate<Trail>()),
time_limit_(model->GetOrCreate<TimeLimit>()),
sat_solver_(model->GetOrCreate<SatSolver>()),
stamping_simplifier_(model->GetOrCreate<StampingSimplifier>()),
model_(model) {}
// Does some simplifications until a fix point is reached or the given
// deterministic time is passed.
bool PresolveLoop(SatPresolveOptions options);
// Simple wrapper that makes sure all the clauses are attached before a
// propagation is performed.
bool LevelZeroPropagate();
// Detects equivalences in the implication graph and propagates any failed
// literal found during the process.
bool DetectEquivalencesAndStamp(bool log_info);
// Removes fixed variables and exploit equivalence relations to cleanup the
// clauses. Returns false if UNSAT.
bool RemoveFixedAndEquivalentVariables(bool log_info);
// Returns true if there is new fixed variables or new equivalence relations
// since RemoveFixedAndEquivalentVariables() was last called.
bool MoreFixedVariableToClean() const;
bool MoreRedundantVariableToClean() const;
// Processes all clauses and see if there is any subsumption/strenghtening
// reductions that can be performed. Returns false if UNSAT.
bool SubsumeAndStrenghtenRound(bool log_info);
private:
const VariablesAssignment& assignment_;
BinaryImplicationGraph* implication_graph_;
LiteralWatchers* clause_manager_;
Trail* trail_;
TimeLimit* time_limit_;
SatSolver* sat_solver_;
StampingSimplifier* stamping_simplifier_;
// TODO(user): This is only used for calling probing. We should probably
// create a Probing class to wraps its data. This will also be needed to not
// always probe the same variables in each round if the deterministic time
// limit is low.
Model* model_;
// Last since clause database was cleaned up.
int64 last_num_redundant_literals_ = 0;
int64 last_num_fixed_variables_ = 0;
};
// Implements "stamping" as described in "Efficient CNF Simplification based on
// Binary Implication Graphs", Marijn Heule, Matti Jarvisalo and Armin Biere.
//
// This sample the implications graph with a spanning tree, and then simplify
// all clauses (subsumption / strengthening) using the implications encoded in
// this tree. So this allows to consider chain of implications instead of just
// direct ones, but depending on the problem, only a small fraction of the
// implication graph will be captured by the tree.
//
// Note that we randomize the spanning tree at each call. This can benefit by
// having the implication graph be transitively reduced before.
class StampingSimplifier {
public:
explicit StampingSimplifier(Model* model)
: implication_graph_(model->GetOrCreate<BinaryImplicationGraph>()),
clause_manager_(model->GetOrCreate<LiteralWatchers>()),
random_(model->GetOrCreate<ModelRandomGenerator>()),
time_limit_(model->GetOrCreate<TimeLimit>()) {}
// This is "fast" (linear scan + sort of all clauses) so we always complete
// the full round.
//
// TODO(user): To save one scan over all the clauses, we could do the fixed
// and equivalence variable cleaning here too.
bool DoOneRound(bool log_info);
// When we compute stamps, we might detect fixed variable (via failed literal
// probing in the implication graph). So it might make sense to do that until
// we have dealt with all fixed literals before calling DoOneRound().
bool ComputeStampsForNextRound(bool log_info);
// Visible for testing.
void SampleTreeAndFillParent();
// Using a DFS visiting order, we can answer reachability query in O(1) on a
// tree, this is well known. ComputeStamps() also detect failed literal in
// the tree and fix them. It can return false on UNSAT.
bool ComputeStamps();
bool ImplicationIsInTree(Literal a, Literal b) const {
return first_stamps_[a.Index()] < first_stamps_[b.Index()] &&
last_stamps_[b.Index()] < last_stamps_[a.Index()];
}
bool ProcessClauses();
private:
BinaryImplicationGraph* implication_graph_;
LiteralWatchers* clause_manager_;
ModelRandomGenerator* random_;
TimeLimit* time_limit_;
// For ComputeStampsForNextRound().
bool stamps_are_already_computed_ = false;
// Reset at each round.
double dtime_ = 0.0;
int64 num_subsumed_clauses_ = 0;
int64 num_removed_literals_ = 0;
int64 num_fixed_ = 0;
// Encode a spanning tree of the implication graph.
gtl::ITIVector<LiteralIndex, LiteralIndex> parents_;
// Adjacency list representation of the parents_ tree.
gtl::ITIVector<LiteralIndex, int> sizes_;
gtl::ITIVector<LiteralIndex, int> starts_;
std::vector<LiteralIndex> children_;
// Temporary data for the DFS.
gtl::ITIVector<LiteralIndex, bool> marked_;
std::vector<LiteralIndex> dfs_stack_;
// First/Last visited index in a DFS of the tree above.
gtl::ITIVector<LiteralIndex, int> first_stamps_;
gtl::ITIVector<LiteralIndex, int> last_stamps_;
};
} // namespace sat
} // namespace operations_research
#endif // OR_TOOLS_SAT_SAT_INPROCESSING_H_