116 lines
5.0 KiB
C++
116 lines
5.0 KiB
C++
// Copyright 2010-2025 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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#ifndef ORTOOLS_SAT_SAT_SWEEPING_H_
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#define ORTOOLS_SAT_SAT_SWEEPING_H_
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#include <cstdint>
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#include <functional>
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#include <utility>
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#include <vector>
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#include "absl/container/flat_hash_map.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_solver.h"
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#include "ortools/sat/util.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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// This is a heuristic to find pairs of equivalent literals as described in [1].
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// The idea is to pick a random variable and define a neighborhood of clauses
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// and variables close to this variable. Next we define a local model containing
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// only those variables and clauses. Since this model is just a smaller portion
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// of the original model, we can expect it to have several feasible solutions.
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// Each solution we find reduces the set of possible equivalent variables. For
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// example, finding two solutions {l1=0, l2=0, ...} and {l1=0, l2=1, ...}
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// implies that `l1` and `l2` are not equivalent. This is done systematically by
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// keeping a partitioning of variables into potential clusters, and solving the
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// local model each time with the right assumptions to either refine a partition
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// or prove that a pair of literals are equivalent. This continue until we are
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// sure to have found all the equivalences.
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//
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// [1] "Clausal Equivalence Sweeping", Armin Biere, Katalin Fazekas, Mathias
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// Fleury, Nils Froleyks, 2025.
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class EquivalenceSatSweeping {
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public:
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explicit EquivalenceSatSweeping(Model* model)
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: sat_solver_(model->GetOrCreate<SatSolver>()),
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implication_graph_(model->GetOrCreate<BinaryImplicationGraph>()),
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clause_manager_(model->GetOrCreate<ClauseManager>()),
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clause_id_generator_(model->GetOrCreate<ClauseIdGenerator>()),
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global_time_limit_(model->GetOrCreate<TimeLimit>()),
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random_(model->GetOrCreate<ModelRandomGenerator>()) {}
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// Do one round of equivalence SAT sweeping.
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// `run_inprocessing` is a function that is called on the model before solving
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// it for the first time. It is useful to call inprocessing without creating a
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// dependency cycle.
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bool DoOneRound(std::function<void(Model*)> run_inprocessing);
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private:
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std::vector<absl::Span<const Literal>> GetNeighborhood(BooleanVariable var);
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void LoadClausesInModel(absl::Span<const SatClause* const> clauses, Model* m);
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SatSolver* sat_solver_;
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BinaryImplicationGraph* implication_graph_;
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ClauseManager* clause_manager_;
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ClauseIdGenerator* clause_id_generator_;
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TimeLimit* global_time_limit_;
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ModelRandomGenerator* random_;
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int max_num_clauses_ = 32000;
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int max_num_boolean_variables_ = 1000;
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// We compute the occurrence graph once at the beginning of each round.
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util_intops::StrongVector<ClauseIndex, absl::Span<const Literal>> clauses_;
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CompactVectorVector<BooleanVariable, ClauseIndex> var_to_clauses_;
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absl::flat_hash_map<BooleanVariable, BooleanVariable>
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big_model_to_small_model_;
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util_intops::StrongVector<BooleanVariable, BooleanVariable>
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small_model_to_big_model_;
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};
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// Do a full SAT sweeping on the model defined by the clauses.
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// The `status` of the result is either FEASIBLE, INFEASIBLE or LIMIT_REACHED.
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// If the result is LIMIT_REACHED, the returned clauses are valid, but they are
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// not exhaustive. If the result is FEASIBLE, all possible binary clauses that
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// define equivalences and all possible unary clauses of the model are
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// guaranteed to be either in the `clauses` input or in the output. Many binary
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// clauses that are not equivalences will be returned too, but not necessarily
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// all of them. This call increases the deterministic time of the `time_limit`.
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struct SatSweepingResult {
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// Literals that if are set to false make the problem unsat.
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std::vector<Literal> unary_clauses;
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// Pairs of literals that if are both set to false make the problem unsat.
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// We filter out the clauses that are already in the input.
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std::vector<std::pair<Literal, Literal>> binary_clauses;
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// TODO(user): also return small clauses of size > 2?
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SatSolver::Status status;
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};
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SatSweepingResult DoFullSatSweeping(
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const CompactVectorVector<int, Literal>& clauses, TimeLimit* time_limit,
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std::function<void(Model*)> configure_model_before_first_solve);
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} // namespace sat
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} // namespace operations_research
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#endif // ORTOOLS_SAT_SAT_SWEEPING_H_
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