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https://github.com/Z3Prover/z3
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6ac3075022
This is another PR towards the goal of getting Z3 to compile cleanly when included via FetchContents into clang-tidy, which uses a pretty strict set of warnings. This is a second version of https://github.com/Z3Prover/z3/pull/9957. I address @NikolajBjorner 's comments about not changing the semicolons after macro invocations, because some editors work better with them present. It now, to the best of my ability, only deletes semis: * after the closing brace of namespace decl. * after the closing brace of an extern "C" decl. * after a function definition. This PR is very large, but it consists entirely of deletions of semicolons in these situations. (If there was a way to update the previous PR, which had been closed, and that is preferable, please let me know. I couldn't figure it out.)
80 lines
2.4 KiB
C++
80 lines
2.4 KiB
C++
/*++
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Copyright (c) 2014 Microsoft Corporation
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Module Name:
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opt_lns.h
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Abstract:
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"large" neighborhood search for maxsat problem instances.
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Start with a model that we assume satisfies at least one of the soft constraint assumptions.
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Attempt to improve the model locally by invoking the SAT solver with a phase
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fixed to be the assignment that solved the previous instance.
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Local improvement is performed by hardening each soft constraint in turn.
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The soft constraints are assumed sorted by weight, such that the highest
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weight soft constraint is first, followed by soft constraints of lower weight.
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Author:
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Nikolaj Bjorner (nbjorner) 2021-02-01
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--*/
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#pragma once
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namespace opt {
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class lns_context {
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public:
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virtual ~lns_context() = default;
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virtual void update_model(model_ref& mdl) = 0;
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virtual void relax_cores(vector<expr_ref_vector> const& cores) = 0;
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virtual rational cost(model& mdl) = 0;
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virtual rational weight(expr* e) = 0;
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virtual expr_ref_vector const& soft() = 0;
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};
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class lns {
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ast_manager& m;
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solver& s;
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lns_context& ctx;
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random_gen m_rand;
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expr_ref_vector m_hardened;
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expr_ref_vector m_unprocessed;
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unsigned m_max_conflicts { 10000 };
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unsigned m_num_improves { 0 };
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bool m_cores_are_valid { true };
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bool m_enable_scoped_bounding { false };
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unsigned m_best_bound { 0 };
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rational m_best_cost;
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model_ref m_best_model;
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scoped_ptr<solver::phase> m_best_phase;
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vector<expr_ref_vector> m_cores;
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expr_mark m_in_core;
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expr_mark m_is_assumption;
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struct scoped_bounding;
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void update_best_model(model_ref& mdl);
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void improve_bs();
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void improve_bs1();
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void apply_best_model();
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expr* unprocessed(unsigned i) const { return m_unprocessed[i]; }
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void set_lns_params();
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void save_defaults(params_ref& p);
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unsigned improve_step(model_ref& mdl);
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lbool improve_step(model_ref& mdl, expr* e);
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void relax_cores();
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unsigned improve_linear(model_ref& mdl);
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public:
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lns(solver& s, lns_context& ctx);
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void set_conflicts(unsigned c) { m_max_conflicts = c; }
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unsigned climb(model_ref& mdl);
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};
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}
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