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include chronological backtracking, two-phase sat, xor inprocessing, probsat, ddfw

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Signed-off-by: Nikolaj Bjorner <nbjorner@microsoft.com>
This commit is contained in:
Nikolaj Bjorner 2019-06-13 03:34:31 -07:00
parent 46d23ea8d7
commit d17248821a
32 changed files with 3246 additions and 654 deletions
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73
src/sat/sat_local_search.h
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@ -36,6 +36,7 @@ namespace sat {
local_search_mode m_mode;
bool m_phase_sticky;
bool m_dbg_flips;
double m_itau;
friend class local_search;
@ -53,6 +54,7 @@ namespace sat {
m_mode = local_search_mode::wsat;
m_phase_sticky = false;
m_dbg_flips = false;
m_itau = 0.5;
}
unsigned random_seed() const { return m_random_seed; }
@ -60,6 +62,7 @@ namespace sat {
local_search_mode mode() const { return m_mode; }
bool phase_sticky() const { return m_phase_sticky; }
bool dbg_flips() const { return m_dbg_flips; }
double itau() const { return m_itau; }
void set_random_seed(unsigned s) { m_random_seed = s; }
void set_best_known_value(unsigned v) { m_best_known_value = v; }
@ -67,7 +70,7 @@ namespace sat {
};
class local_search {
class local_search : public i_local_search {
struct pbcoeff {
unsigned m_constraint_id;
@ -102,6 +105,7 @@ namespace sat {
literal_vector m_bin[2];
unsigned m_flips;
ema m_slow_break;
double m_break_prob;
var_info():
m_value(true),
m_bias(50),
@ -111,7 +115,8 @@ namespace sat {
m_score(0),
m_slack_score(0),
m_flips(0),
m_slow_break(1e-5)
m_slow_break(1e-5),
m_break_prob(0)
{}
};
@ -134,6 +139,7 @@ namespace sat {
local_search_config m_config;
vector<var_info> m_vars; // variables
svector<bool> m_best_phase; // best value in round
svector<bool_var> m_units; // unit clauses
vector<constraint> m_constraints; // all constraints
literal_vector m_assumptions; // temporary assumptions
@ -167,7 +173,6 @@ namespace sat {
parallel* m_par;
model m_model;
inline int score(bool_var v) const { return m_vars[v].m_score; }
inline void inc_score(bool_var v) { m_vars[v].m_score++; }
inline void dec_score(bool_var v) { m_vars[v].m_score--; }
@ -223,48 +228,58 @@ namespace sat {
void extract_model();
void add_clause(unsigned sz, literal const* c);
void add_unit(literal lit, literal explain);
std::ostream& display(std::ostream& out) const;
std::ostream& display(std::ostream& out, constraint const& c) const;
std::ostream& display(std::ostream& out, unsigned v, var_info const& vi) const;
lbool check();
unsigned num_vars() const { return m_vars.size() - 1; } // var index from 1 to num_vars
public:
local_search();
reslimit& rlimit() { return m_limit; }
~local_search() override;
reslimit& rlimit() override { return m_limit; }
~local_search();
lbool check(unsigned sz, literal const* assumptions, parallel* p) override;
unsigned num_non_binary_clauses() const override { return m_num_non_binary_clauses; }
void add(solver const& s) override { import(s, false); }
model const& get_model() const override { return m_model; }
void collect_statistics(statistics& st) const override;
void updt_params(params_ref const& p) override {}
void set_seed(unsigned n) override { config().set_random_seed(n); }
void reinit(solver& s) override;
// used by unit-walk
void set_phase(bool_var v, bool f);
void set_bias(bool_var v, lbool f);
bool get_best_phase(bool_var v) const { return m_best_phase[v]; }
inline bool cur_solution(bool_var v) const { return m_vars[v].m_value; }
double get_priority(bool_var v) const override { return m_vars[v].m_break_prob; }
void import(solver const& s, bool init);
void add_cardinality(unsigned sz, literal const* c, unsigned k);
void add_pb(unsigned sz, literal const* c, unsigned const* coeffs, unsigned k);
lbool check();
lbool check(unsigned sz, literal const* assumptions, parallel* p = nullptr);
local_search_config& config() { return m_config; }
unsigned num_vars() const { return m_vars.size() - 1; } // var index from 1 to num_vars
unsigned num_non_binary_clauses() const { return m_num_non_binary_clauses; }
void import(solver& s, bool init);
void set_phase(bool_var v, lbool f);
void set_bias(bool_var v, lbool f);
bool get_phase(bool_var v) const { return is_true(v); }
inline bool cur_solution(bool_var v) const { return m_vars[v].m_value; }
double break_count(bool_var v) const { return m_vars[v].m_slow_break; }
model& get_model() { return m_model; }
void collect_statistics(statistics& st) const;
};
}