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revise local search

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Signed-off-by: Nikolaj Bjorner <nbjorner@microsoft.com>
This commit is contained in:
Nikolaj Bjorner 2019-02-11 13:14:20 -08:00
parent 22783a4bcb
commit 5fe40a25dc
3 changed files with 159 additions and 486 deletions
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163
src/sat/sat_local_search.h
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@ -36,6 +36,16 @@ namespace sat {
local_search_mode m_mode;
bool m_phase_sticky;
bool m_dbg_flips;
friend class local_search;
void set_config(config const& cfg) {
m_mode = cfg.m_local_search_mode;
m_random_seed = cfg.m_random_seed;
m_phase_sticky = cfg.m_phase_sticky;
m_dbg_flips = cfg.m_local_search_dbg_flips;
}
public:
local_search_config() {
m_random_seed = 0;
@ -54,12 +64,6 @@ namespace sat {
void set_random_seed(unsigned s) { m_random_seed = s; }
void set_best_known_value(unsigned v) { m_best_known_value = v; }
void set_config(config const& cfg) {
m_mode = cfg.m_local_search_mode;
m_random_seed = cfg.m_random_seed;
m_phase_sticky = cfg.m_phase_sticky;
m_dbg_flips = cfg.m_local_search_dbg_flips;
}
};
@ -74,12 +78,6 @@ namespace sat {
typedef svector<bool> bool_vector;
typedef svector<pbcoeff> coeff_vector;
// data structure for a term in objective function
struct ob_term {
bool_var var_id; // variable id, begin with 1
int coefficient; // non-zero integer
ob_term(bool_var v, int c): var_id(v), coefficient(c) {}
};
struct stats {
unsigned m_num_flips;
@ -93,12 +91,12 @@ namespace sat {
unsigned m_bias; // bias for current solution in percentage.
// if bias is 0, then value is always false, if 100, then always true
bool m_unit; // is this a unit literal
literal m_explain; // explanation for unit assignment
bool m_conf_change; // whether its configure changes since its last flip
bool m_in_goodvar_stack;
int m_score;
int m_slack_score;
int m_time_stamp; // the flip time stamp
int m_cscc; // how many times its constraint state configure changes since its last flip
bool_var_vector m_neighbors; // neighborhood variables
coeff_vector m_watch[2];
literal_vector m_bin[2];
@ -112,7 +110,6 @@ namespace sat {
m_in_goodvar_stack(false),
m_score(0),
m_slack_score(0),
m_cscc(0),
m_flips(0),
m_slow_break(1e-5)
{}
@ -132,19 +129,44 @@ namespace sat {
literal const* end() const { return m_literals.end(); }
};
stats m_stats;
local_search_config m_config;
// objective function: maximize
svector<ob_term> ob_constraint; // the objective function *constraint*, sorted in descending order
// information about the variable
int_vector coefficient_in_ob_constraint; // var! initialized to be 0
stats m_stats;
local_search_config m_config;
vector<var_info> m_vars; // variables
svector<bool_var> m_units; // unit clauses
vector<constraint> m_constraints; // all constraints
literal_vector m_assumptions; // temporary assumptions
literal_vector m_prop_queue; // propagation queue
unsigned m_num_non_binary_clauses;
bool m_is_pb;
bool m_is_unsat;
unsigned_vector m_unsat_stack; // store all the unsat constraints
unsigned_vector m_index_in_unsat_stack; // which position is a constraint in the unsat_stack
// configuration changed decreasing variables (score>0 and conf_change==true)
bool_var_vector m_goodvar_stack;
bool m_initializing;
// information about solution
unsigned m_best_unsat;
double m_best_unsat_rate;
double m_last_best_unsat_rate;
// for non-known instance, set as maximal
int m_best_known_value = INT_MAX; // best known value for this instance
unsigned m_max_steps = (1 << 30);
// dynamic noise
double m_noise = 9800; // normalized by 10000
double m_noise_delta = 0.05;
reslimit m_limit;
random_gen m_rand;
parallel* m_par;
model m_model;
vector<var_info> m_vars;
svector<bool_var> m_units;
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++; }
@ -157,21 +179,10 @@ namespace sat {
inline bool already_in_goodvar_stack(bool_var v) const { return m_vars[v].m_in_goodvar_stack; }
inline bool conf_change(bool_var v) const { return m_vars[v].m_conf_change; }
inline int time_stamp(bool_var v) const { return m_vars[v].m_time_stamp; }
inline int cscc(bool_var v) const { return m_vars[v].m_cscc; }
inline void inc_cscc(bool_var v) { m_vars[v].m_cscc++; }
inline bool cur_solution(bool_var v) const { return m_vars[v].m_value; }
inline void set_best_unsat();
/* TBD: other scores */
vector<constraint> m_constraints;
literal_vector m_assumptions;
literal_vector m_prop_queue;
unsigned m_num_non_binary_clauses;
bool m_is_pb;
inline bool is_pos(literal t) const { return !t.sign(); }
inline bool is_true(bool_var v) const { return cur_solution(v); }
@ -182,101 +193,37 @@ namespace sat {
unsigned num_constraints() const { return m_constraints.size(); } // constraint index from 1 to num_constraint
unsigned constraint_slack(unsigned ci) const { return m_constraints[ci].m_slack; }
// unsat constraint stack
bool m_is_unsat;
unsigned_vector m_unsat_stack; // store all the unsat constraints
unsigned_vector m_index_in_unsat_stack; // which position is a constraint in the unsat_stack
// configuration changed decreasing variables (score>0 and conf_change==true)
bool_var_vector m_goodvar_stack;
// information about solution
unsigned m_best_unsat;
double m_best_unsat_rate;
double m_last_best_unsat_rate;
int m_objective_value; // the objective function value corresponds to the current solution
bool_vector m_best_solution; // !var: the best solution so far
int m_best_objective_value = -1; // the objective value corresponds to the best solution so far
// for non-known instance, set as maximal
int m_best_known_value = INT_MAX; // best known value for this instance
unsigned m_max_steps = (1 << 30);
// dynamic noise
double m_noise = 9800; // normalized by 10000
double m_noise_delta = 0.05;
reslimit m_limit;
random_gen m_rand;
parallel* m_par;
model m_model;
void init();
void reinit();
void reinit_orig();
void init_cur_solution();
void init_slack();
void init_scores();
void init_goodvars();
bool_var pick_var_gsat();
void flip_gsat(bool_var v);
void init_goodvars();
void pick_flip_walksat();
void flip_walksat(bool_var v);
bool propagate(literal lit);
void add_propagation(literal lit);
void walksat();
void gsat();
void unsat(unsigned c);
void sat(unsigned c);
bool tie_breaker_sat(bool_var v1, bool_var v2);
bool tie_breaker_ccd(bool_var v1, bool_var v2);
void set_parameters();
void calculate_and_update_ob();
bool all_objectives_are_met() const;
void verify_solution() const;
void verify_unsat_stack() const;
void verify_constraint(constraint const& c) const;
void verify_slack(constraint const& c) const;
void verify_slack() const;
bool verify_goodvar() const;
unsigned constraint_value(constraint const& c) const;
unsigned constraint_coeff(constraint const& c, literal l) const;
void print_info(std::ostream& out);
void extract_model();
bool check_goodvar();
void add_clause(unsigned sz, literal const* c);
void add_unit(literal lit);
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;
public:
@ -287,8 +234,6 @@ namespace sat {
~local_search();
void add_soft(bool_var v, int weight);
void add_cardinality(unsigned sz, literal const* c, unsigned k);
void add_pb(unsigned sz, literal const* c, unsigned const* coeffs, unsigned k);
@ -307,8 +252,14 @@ namespace sat {
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;