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address divergence in the case of shared theory symbols. Codeplex issue 147, thanks to George Karpenkov

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Signed-off-by: Nikolaj Bjorner <nbjorner@microsoft.com>
This commit is contained in:
Nikolaj Bjorner 2014-12-09 16:04:25 +01:00
commit 08cb8b8de8
74 changed files with 1280 additions and 896 deletions
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54
src/opt/opt_solver.cpp
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@ -43,6 +43,7 @@ namespace opt {
m(mgr),
m_dump_benchmarks(false),
m_fm(fm),
m_objective_sorts(m),
m_first(true) {
m_params.updt_params(p);
m_params.m_relevancy_lvl = 0;
@ -173,13 +174,56 @@ namespace opt {
}
/**
\brief maximize the value of objective i in the current state.
Return a predicate that blocks the current maximal value.
The result of 'maximize' is post-processed.
When maximization involves shared symbols the model produced
by local optimization does not necessarily satisfy combination
constraints (it may not be a real model).
In this case, the model is post-processed (update_model
causes an additional call to final_check to propagate theory equalities
when 'has_shared' is true).
*/
void opt_solver::maximize_objective(unsigned i, expr_ref& blocker) {
smt::theory_var v = m_objective_vars[i];
m_objective_values[i] = get_optimizer().maximize(v, blocker);
m_context.get_context().update_model();
bool has_shared = false;
inf_eps val = get_optimizer().maximize(v, blocker, has_shared);
inf_eps val2;
m_valid_objectives[i] = true;
if (m_context.get_context().update_model(has_shared)) {
if (has_shared) {
val2 = current_objective_value(i);
if (val2 != val) {
decrement_value(i, val);
}
}
}
else {
SASSERT(has_shared);
// model is not final. We set the current objective to
// close to the optimal (ignoring types).
decrement_value(i, val);
}
m_objective_values[i] = val;
TRACE("opt", { model_ref mdl; tout << m_objective_values[i] << "\n";
get_model(mdl); model_smt2_pp(tout << "update model: ", m, *mdl, 0); });
tout << blocker << "\n";
get_model(mdl); model_smt2_pp(tout << "update model:\n", m, *mdl, 0); });
}
void opt_solver::decrement_value(unsigned i, inf_eps& val) {
if (arith_util(m).is_real(m_objective_sorts[i].get())) {
val -= inf_eps(inf_rational(rational(0),true));
}
else {
val -= inf_eps(inf_rational(rational(1)));
}
m_valid_objectives[i] = false;
}
void opt_solver::get_unsat_core(ptr_vector<expr> & r) {
unsigned sz = m_context.get_unsat_core_size();
@ -232,6 +276,8 @@ namespace opt {
smt::theory_var v = get_optimizer().add_objective(term);
m_objective_vars.push_back(v);
m_objective_values.push_back(inf_eps(rational(-1), inf_rational()));
m_objective_sorts.push_back(m.get_sort(term));
m_valid_objectives.push_back(true);
return v;
}
@ -278,6 +324,8 @@ namespace opt {
void opt_solver::reset_objectives() {
m_objective_vars.reset();
m_objective_values.reset();
m_objective_sorts.reset();
m_valid_objectives.reset();
}
opt_solver& opt_solver::to_opt(solver& s) {