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fix bounds for weighted maxsmt

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Signed-off-by: Nikolaj Bjorner <nbjorner@microsoft.com>
This commit is contained in:
Nikolaj Bjorner 2013-11-08 21:26:05 -08:00
parent 6e1c186017
commit 21058c38fd
1 changed files with 36 additions and 22 deletions
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58
src/opt/weighted_maxsat.cpp
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@ -27,12 +27,12 @@ namespace smt {
app_ref_vector m_vars; // Auxiliary variables per soft clause
expr_ref_vector m_fmls; // Formulas per soft clause
app_ref m_min_cost_atom; // atom tracking modified lower bound
bool_var m_min_cost_bv; // min cost Boolean variable
bool_var m_min_cost_bv; // max cost Boolean variable
vector<rational> m_weights; // weights of theory variables.
svector<theory_var> m_costs; // set of asserted theory variables
svector<theory_var> m_cost_save; // set of asserted theory variables
rational m_cost; // current sum of asserted costs
rational m_min_cost; // current minimal cost assignment.
rational m_min_cost; // current maximal cost assignment.
u_map<theory_var> m_bool2var; // bool_var -> theory_var
svector<bool_var> m_var2bool; // theory_var -> bool_var
public:
@ -174,9 +174,9 @@ namespace smt {
m_fmls.reset();
m_weights.reset();
m_costs.reset();
m_min_cost.reset();
m_cost.reset();
m_cost_save.reset();
m_min_cost.reset();
m_bool2var.reset();
m_var2bool.reset();
m_min_cost_atom = 0;
@ -240,8 +240,10 @@ namespace smt {
namespace opt {
/**
Iteratively increase min-cost until there is an assignment during
Iteratively increase cost until there is an assignment during
final_check that satisfies min_cost.
Takes: log (n / log(n)) iterations
*/
static lbool iterative_weighted_maxsat(opt_solver& s, smt::theory_weighted_maxsat& wth) {
@ -271,37 +273,43 @@ namespace opt {
opt_solver& s;
expr_ref_vector m_soft;
expr_ref_vector m_assignment;
rational m_lower;
rational m_upper;
rational m_value;
vector<rational> m_weights;
rational m_upper;
imp(ast_manager& m, opt_solver& s, expr_ref_vector& soft_constraints, vector<rational> const& weights):
m(m), s(s), m_soft(soft_constraints), m_assignment(m), m_weights(weights)
{}
~imp() {}
smt::theory_weighted_maxsat& ensure_theory() {
smt::theory_weighted_maxsat* get_theory() const {
smt::context& ctx = s.get_context();
smt::theory_id th_id = m.get_family_id("weighted_maxsat");
smt::theory* th = ctx.get_theory(th_id);
smt::theory_weighted_maxsat* wth;
if (th) {
wth = dynamic_cast<smt::theory_weighted_maxsat*>(th);
return dynamic_cast<smt::theory_weighted_maxsat*>(th);
}
else {
return 0;
}
}
smt::theory_weighted_maxsat& ensure_theory() {
smt::theory_weighted_maxsat* wth = get_theory();
if (wth) {
wth->reset();
}
else {
wth = alloc(smt::theory_weighted_maxsat, m);
ctx.register_plugin(wth);
s.get_context().register_plugin(wth);
}
return *wth;
}
/**
Takes solver with hard constraints added.
Returns a maximal satisfying subset of weighted soft_constraints
that are still consistent with the solver state.
*/
/**
Takes solver with hard constraints added.
Returns a maximal satisfying subset of weighted soft_constraints
that are still consistent with the solver state.
*/
lbool operator()() {
smt::theory_weighted_maxsat& wth = ensure_theory();
@ -322,9 +330,18 @@ namespace opt {
result = l_true;
}
}
m_upper = wth.get_min_cost();
wth.reset();
return result;
}
rational get_lower() const {
return rational(0);
}
rational get_upper() const {
return m_upper;
}
};
wmaxsmt::wmaxsmt(ast_manager& m, opt_solver& s, expr_ref_vector& soft_constraints, vector<rational> const& weights) {
@ -339,16 +356,13 @@ namespace opt {
return (*m_imp)();
}
rational wmaxsmt::get_lower() const {
NOT_IMPLEMENTED_YET();
return m_imp->m_lower;
return m_imp->get_lower();
}
rational wmaxsmt::get_upper() const {
NOT_IMPLEMENTED_YET();
return m_imp->m_upper;
return m_imp->get_upper();
}
rational wmaxsmt::get_value() const {
NOT_IMPLEMENTED_YET();
return m_imp->m_value;
return m_imp->get_upper();
}
expr_ref_vector wmaxsmt::get_assignment() const {
return m_imp->m_assignment;