389 lines
15 KiB
C++
389 lines
15 KiB
C++
// Copyright 2010-2022 Google LLC
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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// This file contains the entry point for our presolve/inprocessing code.
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//
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// TODO(user): for now it is mainly presolve, but the idea is to call these
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// function during the search so they should be as incremental as possible. That
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// is avoid doing work that is not useful because nothing changed or exploring
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// parts that were not done during the last round.
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#ifndef OR_TOOLS_SAT_SAT_INPROCESSING_H_
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#define OR_TOOLS_SAT_SAT_INPROCESSING_H_
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#include <cstdint>
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#include <deque>
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#include <vector>
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#include "absl/strings/string_view.h"
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#include "absl/types/span.h"
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#include "ortools/base/strong_vector.h"
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#include "ortools/sat/clause.h"
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#include "ortools/sat/drat_checker.h"
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#include "ortools/sat/model.h"
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#include "ortools/sat/sat_base.h"
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#include "ortools/sat/sat_decision.h"
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#include "ortools/sat/sat_parameters.pb.h"
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#include "ortools/sat/sat_solver.h"
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#include "ortools/sat/util.h"
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#include "ortools/util/integer_pq.h"
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#include "ortools/util/strong_integers.h"
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#include "ortools/util/time_limit.h"
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namespace operations_research {
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namespace sat {
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// The order is important and each clauses has a "special" literal that is
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// put first.
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//
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// TODO(user): Use a flat memory structure instead.
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struct PostsolveClauses {
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// Utility function that push back clause but also make sure the given literal
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// from clause appear first.
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void AddClauseWithSpecialLiteral(Literal literal,
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absl::Span<const Literal> clause);
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std::deque<std::vector<Literal>> clauses;
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};
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class BlockedClauseSimplifier;
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class BoundedVariableElimination;
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class StampingSimplifier;
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struct SatPresolveOptions {
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// The time budget to spend.
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double deterministic_time_limit = 30.0;
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// We assume this is also true if --v 1 is activated and we actually log
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// even more in --v 1.
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bool log_info = false;
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// See ProbingOptions in probing.h
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bool extract_binary_clauses_in_probing = false;
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// Whether we perform a transitive reduction of the binary implication graph
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// after equivalent literal detection and before each probing pass.
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//
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// TODO(user): Doing that before the current SAT presolve also change the
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// possible reduction. This shouldn't matter if we use the binary implication
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// graph and its reachability instead of just binary clause though.
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bool use_transitive_reduction = false;
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};
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// We need to keep some information from one call to the next, so we use a
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// class. Note that as this becomes big, we can probably split it.
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//
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// TODO(user): Some algorithms here use the normal SAT propagation engine.
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// However we might want to temporarily disable activities/phase saving and so
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// on if we want to run them as in-processing steps so that they
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// do not "pollute" the normal SAT search.
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//
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// TODO(user): For the propagation, this depends on the SatSolver class, which
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// mean we cannot really use it without some refactoring as an in-processing
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// from the SatSolver::Solve() function. So we do need a special
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// InprocessingSolve() that lives outside SatSolver. Alternatively, we can
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// extract the propagation main loop and conflict analysis from SatSolver.
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class Inprocessing {
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public:
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explicit Inprocessing(Model* model)
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: assignment_(model->GetOrCreate<Trail>()->Assignment()),
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implication_graph_(model->GetOrCreate<BinaryImplicationGraph>()),
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clause_manager_(model->GetOrCreate<LiteralWatchers>()),
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trail_(model->GetOrCreate<Trail>()),
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decision_policy_(model->GetOrCreate<SatDecisionPolicy>()),
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time_limit_(model->GetOrCreate<TimeLimit>()),
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sat_solver_(model->GetOrCreate<SatSolver>()),
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stamping_simplifier_(model->GetOrCreate<StampingSimplifier>()),
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blocked_clause_simplifier_(
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model->GetOrCreate<BlockedClauseSimplifier>()),
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bounded_variable_elimination_(
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model->GetOrCreate<BoundedVariableElimination>()),
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model_(model) {}
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// Does some simplifications until a fix point is reached or the given
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// deterministic time is passed.
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bool PresolveLoop(SatPresolveOptions options);
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// When the option use_sat_inprocessing is true, then this is called at each
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// restart. It is up to the heuristics here to decide what inprocessing we
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// do or if we wait for the next call before doing anything.
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bool InprocessingRound();
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// Simple wrapper that makes sure all the clauses are attached before a
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// propagation is performed.
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bool LevelZeroPropagate();
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// Detects equivalences in the implication graph and propagates any failed
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// literal found during the process.
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bool DetectEquivalencesAndStamp(bool use_transitive_reduction, bool log_info);
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// Removes fixed variables and exploit equivalence relations to cleanup the
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// clauses. Returns false if UNSAT.
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bool RemoveFixedAndEquivalentVariables(bool log_info);
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// Returns true if there is new fixed variables or new equivalence relations
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// since RemoveFixedAndEquivalentVariables() was last called.
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bool MoreFixedVariableToClean() const;
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bool MoreRedundantVariableToClean() const;
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// Processes all clauses and see if there is any subsumption/strenghtening
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// reductions that can be performed. Returns false if UNSAT.
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bool SubsumeAndStrenghtenRound(bool log_info);
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private:
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const VariablesAssignment& assignment_;
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BinaryImplicationGraph* implication_graph_;
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LiteralWatchers* clause_manager_;
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Trail* trail_;
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SatDecisionPolicy* decision_policy_;
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TimeLimit* time_limit_;
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SatSolver* sat_solver_;
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StampingSimplifier* stamping_simplifier_;
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BlockedClauseSimplifier* blocked_clause_simplifier_;
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BoundedVariableElimination* bounded_variable_elimination_;
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double total_dtime_ = 0.0;
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// TODO(user): This is only used for calling probing. We should probably
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// create a Probing class to wraps its data. This will also be needed to not
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// always probe the same variables in each round if the deterministic time
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// limit is low.
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Model* model_;
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// Last since clause database was cleaned up.
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int64_t last_num_redundant_literals_ = 0;
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int64_t last_num_fixed_variables_ = 0;
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};
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// Implements "stamping" as described in "Efficient CNF Simplification based on
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// Binary Implication Graphs", Marijn Heule, Matti Jarvisalo and Armin Biere.
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//
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// This sample the implications graph with a spanning tree, and then simplify
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// all clauses (subsumption / strengthening) using the implications encoded in
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// this tree. So this allows to consider chain of implications instead of just
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// direct ones, but depending on the problem, only a small fraction of the
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// implication graph will be captured by the tree.
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//
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// Note that we randomize the spanning tree at each call. This can benefit by
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// having the implication graph be transitively reduced before.
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class StampingSimplifier {
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public:
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explicit StampingSimplifier(Model* model)
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: assignment_(model->GetOrCreate<Trail>()->Assignment()),
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implication_graph_(model->GetOrCreate<BinaryImplicationGraph>()),
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clause_manager_(model->GetOrCreate<LiteralWatchers>()),
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random_(model->GetOrCreate<ModelRandomGenerator>()),
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time_limit_(model->GetOrCreate<TimeLimit>()) {}
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// This is "fast" (linear scan + sort of all clauses) so we always complete
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// the full round.
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//
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// TODO(user): To save one scan over all the clauses, we could do the fixed
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// and equivalence variable cleaning here too.
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bool DoOneRound(bool log_info);
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// When we compute stamps, we might detect fixed variable (via failed literal
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// probing in the implication graph). So it might make sense to do that until
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// we have dealt with all fixed literals before calling DoOneRound().
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bool ComputeStampsForNextRound(bool log_info);
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// Visible for testing.
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void SampleTreeAndFillParent();
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// Using a DFS visiting order, we can answer reachability query in O(1) on a
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// tree, this is well known. ComputeStamps() also detect failed literal in
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// the tree and fix them. It can return false on UNSAT.
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bool ComputeStamps();
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bool ImplicationIsInTree(Literal a, Literal b) const {
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return first_stamps_[a.Index()] < first_stamps_[b.Index()] &&
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last_stamps_[b.Index()] < last_stamps_[a.Index()];
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}
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bool ProcessClauses();
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private:
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const VariablesAssignment& assignment_;
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BinaryImplicationGraph* implication_graph_;
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LiteralWatchers* clause_manager_;
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ModelRandomGenerator* random_;
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TimeLimit* time_limit_;
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// For ComputeStampsForNextRound().
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bool stamps_are_already_computed_ = false;
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// Reset at each round.
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double dtime_ = 0.0;
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int64_t num_subsumed_clauses_ = 0;
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int64_t num_removed_literals_ = 0;
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int64_t num_fixed_ = 0;
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// Encode a spanning tree of the implication graph.
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absl::StrongVector<LiteralIndex, LiteralIndex> parents_;
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// Adjacency list representation of the parents_ tree.
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absl::StrongVector<LiteralIndex, int> sizes_;
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absl::StrongVector<LiteralIndex, int> starts_;
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std::vector<LiteralIndex> children_;
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// Temporary data for the DFS.
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absl::StrongVector<LiteralIndex, bool> marked_;
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std::vector<LiteralIndex> dfs_stack_;
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// First/Last visited index in a DFS of the tree above.
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absl::StrongVector<LiteralIndex, int> first_stamps_;
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absl::StrongVector<LiteralIndex, int> last_stamps_;
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};
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// A clause c is "blocked" by a literal l if all clauses containing the
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// negation of l resolve to trivial clause with c. Blocked clause can be
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// simply removed from the problem. At postsolve, if a blocked clause is not
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// satisfied, then l can simply be set to true without breaking any of the
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// clause containing not(l).
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//
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// See the paper "Blocked Clause Elimination", Matti Jarvisalo, Armin Biere,
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// and Marijn Heule.
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//
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// TODO(user): This requires that l only appear in clauses and not in the
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// integer part of CP-SAT.
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class BlockedClauseSimplifier {
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public:
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explicit BlockedClauseSimplifier(Model* model)
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: assignment_(model->GetOrCreate<Trail>()->Assignment()),
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implication_graph_(model->GetOrCreate<BinaryImplicationGraph>()),
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clause_manager_(model->GetOrCreate<LiteralWatchers>()),
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postsolve_(model->GetOrCreate<PostsolveClauses>()),
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time_limit_(model->GetOrCreate<TimeLimit>()) {}
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void DoOneRound(bool log_info);
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private:
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void InitializeForNewRound();
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void ProcessLiteral(Literal current_literal);
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bool ClauseIsBlocked(Literal current_literal,
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absl::Span<const Literal> clause);
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const VariablesAssignment& assignment_;
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BinaryImplicationGraph* implication_graph_;
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LiteralWatchers* clause_manager_;
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PostsolveClauses* postsolve_;
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TimeLimit* time_limit_;
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double dtime_ = 0.0;
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int32_t num_blocked_clauses_ = 0;
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int64_t num_inspected_literals_ = 0;
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// Temporary vector to mark literal of a clause.
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absl::StrongVector<LiteralIndex, bool> marked_;
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// List of literal to process.
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// TODO(user): use priority queue?
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absl::StrongVector<LiteralIndex, bool> in_queue_;
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std::deque<Literal> queue_;
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// We compute the occurrence graph just once at the beginning of each round
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// and we do not shrink it as we remove blocked clauses.
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DEFINE_STRONG_INDEX_TYPE(rat_literal_clause_index);
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absl::StrongVector<ClauseIndex, SatClause*> clauses_;
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absl::StrongVector<LiteralIndex, std::vector<ClauseIndex>>
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literal_to_clauses_;
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};
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class BoundedVariableElimination {
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public:
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explicit BoundedVariableElimination(Model* model)
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: parameters_(*model->GetOrCreate<SatParameters>()),
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assignment_(model->GetOrCreate<Trail>()->Assignment()),
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implication_graph_(model->GetOrCreate<BinaryImplicationGraph>()),
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clause_manager_(model->GetOrCreate<LiteralWatchers>()),
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postsolve_(model->GetOrCreate<PostsolveClauses>()),
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trail_(model->GetOrCreate<Trail>()),
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time_limit_(model->GetOrCreate<TimeLimit>()) {}
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bool DoOneRound(bool log_info);
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private:
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int NumClausesContaining(Literal l);
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void UpdatePriorityQueue(BooleanVariable var);
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bool CrossProduct(BooleanVariable var);
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void DeleteClause(SatClause* sat_clause);
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void DeleteAllClausesContaining(Literal literal);
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void AddClause(absl::Span<const Literal> clause);
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bool RemoveLiteralFromClause(Literal lit, SatClause* sat_clause);
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bool Propagate();
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// The actual clause elimination algo. We have two versions, one just compute
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// the "score" of what will be the final state. The other perform the
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// resolution, remove old clauses and add the new ones.
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//
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// Returns false on UNSAT.
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template <bool score_only, bool with_binary_only>
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bool ResolveAllClauseContaining(Literal lit);
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const SatParameters& parameters_;
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const VariablesAssignment& assignment_;
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BinaryImplicationGraph* implication_graph_;
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LiteralWatchers* clause_manager_;
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PostsolveClauses* postsolve_;
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Trail* trail_;
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TimeLimit* time_limit_;
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int propagation_index_;
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double dtime_ = 0.0;
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int64_t num_inspected_literals_ = 0;
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int64_t num_simplifications_ = 0;
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int64_t num_blocked_clauses_ = 0;
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int64_t num_eliminated_variables_ = 0;
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int64_t num_literals_diff_ = 0;
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int64_t num_clauses_diff_ = 0;
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int64_t new_score_;
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int64_t score_threshold_;
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// Temporary vector to mark literal of a clause and compute its resolvant.
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absl::StrongVector<LiteralIndex, bool> marked_;
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std::vector<Literal> resolvant_;
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// Priority queue of variable to process.
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// We will process highest priority first.
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struct VariableWithPriority {
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BooleanVariable var;
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int32_t priority;
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// Interface for the IntegerPriorityQueue.
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int Index() const { return var.value(); }
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bool operator<(const VariableWithPriority& o) const {
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return priority < o.priority;
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}
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};
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IntegerPriorityQueue<VariableWithPriority> queue_;
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// We update the queue_ in batch.
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absl::StrongVector<BooleanVariable, bool> in_need_to_be_updated_;
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std::vector<BooleanVariable> need_to_be_updated_;
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// We compute the occurrence graph just once at the beginning of each round.
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// We maintains the sizes at all time and lazily shrink the graph with deleted
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// clauses.
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DEFINE_STRONG_INDEX_TYPE(ClauseIndex);
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absl::StrongVector<ClauseIndex, SatClause*> clauses_;
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absl::StrongVector<LiteralIndex, std::vector<ClauseIndex>>
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literal_to_clauses_;
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absl::StrongVector<LiteralIndex, int> literal_to_num_clauses_;
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};
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} // namespace sat
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} // namespace operations_research
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#endif // OR_TOOLS_SAT_SAT_INPROCESSING_H_
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