z3-z3-4.12.6.src.smt.theory_wmaxsat.h Maven / Gradle / Ivy
/*++
Copyright (c) 2013 Microsoft Corporation
Module Name:
theory_wmaxsat.h
Abstract:
Weighted Max-SAT theory plugin.
Author:
Nikolaj Bjorner (nbjorner) 2013-11-05
Notes:
--*/
#pragma once
#include "smt/smt_theory.h"
#include "smt/smt_clause.h"
#include "ast/converters/generic_model_converter.h"
namespace smt {
class theory_wmaxsat : public theory {
struct stats {
unsigned m_num_blocks;
unsigned m_num_propagations;
void reset() { memset(this, 0, sizeof(*this)); }
stats() { reset(); }
};
generic_model_converter& m_mc;
mutable unsynch_mpz_manager m_mpz;
app_ref_vector m_vars; // Auxiliary variables per soft clause
expr_ref_vector m_fmls; // Formulas per soft clause
vector m_rweights; // weights of theory variables.
scoped_mpz_vector m_zweights;
scoped_mpz_vector m_old_values;
svector m_costs; // set of asserted theory variables
unsigned m_max_unassigned_index; // index of literal that is not yet assigned and has maximal weight.
svector m_sorted_vars; // set of all theory variables, sorted by cost
svector m_cost_save; // set of asserted theory variables
rational m_rmin_cost; // current maximal cost assignment.
scoped_mpz m_zcost; // current sum of asserted costs
scoped_mpz m_zmin_cost; // current maximal cost assignment.
bool m_found_optimal;
u_map m_bool2var; // bool_var -> theory_var
svector m_var2bool; // theory_var -> bool_var
bool m_propagate;
bool m_can_propagate;
bool m_normalize;
rational m_den; // lcm of denominators for rational weights.
bool_vector m_assigned, m_enabled;
stats m_stats;
public:
theory_wmaxsat(context& ctx, ast_manager& m, generic_model_converter& mc);
~theory_wmaxsat() override;
void get_assignment(bool_vector& result);
expr* assert_weighted(expr* fml, rational const& w);
void disable_var(expr* var);
bool_var register_var(app* var, bool attach);
rational get_cost();
void init_min_cost(rational const& r);
class numeral_trail : public trail {
typedef scoped_mpz T;
T & m_value;
scoped_mpz_vector& m_old_values;
public:
numeral_trail(T & value, scoped_mpz_vector& old):
m_value(value),
m_old_values(old) {
old.push_back(value);
}
void undo() override {
m_value = m_old_values.back();
m_old_values.shrink(m_old_values.size() - 1);
}
};
void init_search_eh() override;
void assign_eh(bool_var v, bool is_true) override;
final_check_status final_check_eh() override;
bool use_diseqs() const override {
return false;
}
bool build_models() const override {
return false;
}
void reset_local();
void reset_eh() override;
theory * mk_fresh(context * new_ctx) override { return nullptr; }
bool internalize_atom(app * atom, bool gate_ctx) override { return false; }
bool internalize_term(app * term) override { return false; }
void new_eq_eh(theory_var v1, theory_var v2) override { }
void new_diseq_eh(theory_var v1, theory_var v2) override { }
void display(std::ostream& out) const override {}
void restart_eh() override;
void collect_statistics(::statistics & st) const override {
st.update("wmaxsat num blocks", m_stats.m_num_blocks);
st.update("wmaxsat num props", m_stats.m_num_propagations);
}
bool can_propagate() override {
return m_propagate || m_can_propagate;
}
void propagate() override;
bool is_optimal() const;
expr_ref mk_block();
private:
void block();
void propagate(bool_var v);
void normalize();
bool max_unassigned_is_blocked();
class compare_cost {
theory_wmaxsat& m_th;
public:
compare_cost(theory_wmaxsat& t):m_th(t) {}
bool operator() (theory_var v, theory_var w) const {
return m_th.m_mpz.gt(m_th.m_zweights[v], m_th.m_zweights[w]);
}
};
};
};