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https://github.com/Z3Prover/z3
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MSS based MaxSMT solver
This commit is contained in:
TheRealNebus
parent
a231ff3735
commit
3bbc09c1d2
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@ -21,6 +21,7 @@ Notes:
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#include "opt/maxsmt.h"
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#include "opt/maxres.h"
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#include "opt/wmax.h"
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#include "opt/mss_solver.h"
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#include "ast/ast_pp.h"
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#include "util/uint_set.h"
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#include "opt/opt_context.h"
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@ -240,6 +241,9 @@ namespace opt {
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else if (maxsat_engine == symbol("pd-maxres")) {
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m_msolver = mk_primal_dual_maxres(m_c, m_index, m_weights, m_soft_constraints);
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}
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else if (maxsat_engine == symbol("mss")) {
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m_msolver = mk_mss_solver(m_c, m_index, m_weights, m_soft_constraints);
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}
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else if (maxsat_engine == symbol("wmax")) {
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m_msolver = mk_wmax(m_c, m_weights, m_soft_constraints);
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}
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156
src/opt/mss_solver.cpp
Executable file
156
src/opt/mss_solver.cpp
Executable file
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@ -0,0 +1,156 @@
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#include "solver/solver.h"
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#include "opt/maxsmt.h"
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#include "opt/mss_solver.h"
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#include "opt/mss.h"
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#include "opt/opt_context.h"
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#include "opt/opt_params.hpp"
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using namespace opt;
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class mss_solver: public maxsmt_solver_base {
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private:
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typedef ptr_vector<expr> exprs;
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mss m_mss;
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unsigned m_index;
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expr_ref_vector m_asms;
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unsigned m_max_mss;
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public:
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mss_solver(maxsat_context& c, unsigned id, weights_t& ws, expr_ref_vector const& soft):
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maxsmt_solver_base(c, ws, soft),
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m_mss(c.get_solver(), m),
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m_index(id),
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m_asms(m),
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m_max_mss(UINT_MAX) {
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}
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virtual ~mss_solver() {}
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virtual lbool operator()() {
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if (!init()) return l_undef;
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init_asms();
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lbool is_sat = check_sat(m_asms);
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if (is_sat == l_undef) return l_undef;
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if (is_sat == l_true) {
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IF_VERBOSE(2, verbose_stream() << "(opt.mss-solver :mss " << m_asms.size() << " :mcs " << 0 << ")\n";);
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model_ref mdl;
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s().get_model(mdl);
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update_assignment(mdl.get());
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return l_true;
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}
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return enumerate_mss();
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}
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virtual void updt_params(params_ref& p) {
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maxsmt_solver_base::updt_params(p);
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opt_params _p(p);
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m_max_mss = _p.mss_max();
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}
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private:
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void init_asms() {
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m_asms.reset();
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for (unsigned i = 0; i < m_soft.size(); ++i) {
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expr* e = m_soft[i];
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m_asms.push_back(relax_and_assert(e));
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}
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}
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expr_ref relax_and_assert(expr* e) {
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expr_ref asum(m);
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if (is_literal(e)) {
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asum = e;
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}
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else {
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asum = mk_fresh_bool("r");
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e = m.mk_iff(asum, e);
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s().assert_expr(e);
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}
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return asum;
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}
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bool is_literal(expr* l) {
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return is_uninterp_const(l) || (m.is_not(l, l) && is_uninterp_const(l));
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}
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lbool enumerate_mss() {
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expr_ref_vector asms(m);
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for (unsigned i = 0; i < m_max_mss; ++i) {
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exprs mss, mcs;
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lbool is_sat = next_mss(asms, mss, mcs);
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if (is_sat == l_false && i == 0) return l_false;
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if (is_sat == l_undef && i == 0) return l_undef;
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if (is_sat == l_false || is_sat == l_undef) return l_true;
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asms.push_back(relax_and_assert(m.mk_or(mcs.size(), mcs.c_ptr())));
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}
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return l_true;
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}
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lbool next_mss(expr_ref_vector const& asms, exprs& mss, exprs& mcs) {
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mss.reset();
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mcs.reset();
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lbool is_sat = check_sat(asms);
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if (is_sat != l_true) return is_sat;
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model_ref mdl;
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s().get_model(mdl);
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update_assignment(mdl.get());
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vector<exprs> dummy;
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push_exprs(mss, m_asms);
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push_exprs(mss, asms);
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is_sat = m_mss(mdl.get(), dummy, mss, mcs);
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SASSERT(is_sat == l_true);
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mdl.reset();
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m_mss.get_model(mdl);
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update_assignment(mdl.get());
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IF_VERBOSE(2, verbose_stream() << "(opt.mss-solver :mss " << mss.size() - asms.size() << " :mcs " << mcs.size() << ")\n";);
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return is_sat;
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}
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void push_exprs(exprs& dst, expr_ref_vector const& src) {
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for (unsigned i = 0; i < src.size(); ++i) {
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dst.push_back(src[i]);
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}
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}
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lbool check_sat() {
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expr_ref_vector dummy(m);
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return check_sat(dummy);
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}
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lbool check_sat(expr_ref_vector const& asms) {
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return s().check_sat(asms);
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}
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void update_assignment(model* mdl) {
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rational upper(0);
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for (unsigned i = 0; i < m_soft.size(); ++i) {
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if (!is_true(mdl, m_soft[i])) {
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upper += m_weights[i];
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}
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}
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if (upper > m_upper) return;
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if (!m_c.verify_model(m_index, mdl, upper)) return;
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m_model = mdl;
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m_c.model_updated(mdl);
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for (unsigned i = 0; i < m_soft.size(); ++i) {
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m_assignment[i] = is_true(m_soft[i]);
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}
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// TODO: DEBUG verify assignment
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m_upper = upper;
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trace_bounds("mss-solver");
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}
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bool is_true(model* mdl, expr* e) {
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expr_ref tmp(m);
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return mdl->eval(e, tmp, true) && m.is_true(tmp);
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}
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bool is_true(expr* e) {
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return is_true(m_model.get(), e);
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}
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};
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maxsmt_solver_base* opt::mk_mss_solver(maxsat_context& c, unsigned id, weights_t& ws, expr_ref_vector const& soft) {
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return alloc(mss_solver, c, id, ws, soft);
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}
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12
src/opt/mss_solver.h
Executable file
12
src/opt/mss_solver.h
Executable file
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@ -0,0 +1,12 @@
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#ifndef MSS_SOLVER_H_
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#define MSS_SOLVER_H_
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#include "opt/maxsmt.h"
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namespace opt {
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maxsmt_solver_base* mk_mss_solver(maxsat_context& c, unsigned id, weights_t& ws, expr_ref_vector const& soft);
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}
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#endif
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@ -2,13 +2,13 @@ def_module_params('opt',
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description='optimization parameters',
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export=True,
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params=(('optsmt_engine', SYMBOL, 'basic', "select optimization engine: 'basic', 'farkas', 'symba'"),
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('maxsat_engine', SYMBOL, 'maxres', "select engine for maxsat: 'core_maxsat', 'wmax', 'maxres', 'pd-maxres'"),
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('maxsat_engine', SYMBOL, 'maxres', "select engine for maxsat: 'core_maxsat', 'wmax', 'maxres', 'pd-maxres', 'mss'"),
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('priority', SYMBOL, 'lex', "select how to priortize objectives: 'lex' (lexicographic), 'pareto', or 'box'"),
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('dump_benchmarks', BOOL, False, 'dump benchmarks for profiling'),
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('solution_prefix', SYMBOL, '', "path prefix to dump intermediary, but non-optimal, solutions"),
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('timeout', UINT, UINT_MAX, 'timeout (in milliseconds) (UINT_MAX and 0 mean no timeout)'),
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('rlimit', UINT, 0, 'resource limit (0 means no limit)'),
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('enable_sls', BOOL, False, 'enable SLS tuning during weighted maxsast'),
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('enable_sls', BOOL, False, 'enable SLS tuning during weighted maxsat'),
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('enable_sat', BOOL, True, 'enable the new SAT core for propositional constraints'),
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('elim_01', BOOL, True, 'eliminate 01 variables'),
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('pp.neat', BOOL, True, 'use neat (as opposed to less readable, but faster) pretty printer when displaying context'),
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@ -20,8 +20,8 @@ def_module_params('opt',
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('maxres.maximize_assignment', BOOL, False, 'find an MSS/MCS to improve current assignment'),
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('maxres.max_correction_set_size', UINT, 3, 'allow generating correction set constraints up to maximal size'),
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('maxres.wmax', BOOL, False, 'use weighted theory solver to constrain upper bounds'),
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('maxres.pivot_on_correction_set', BOOL, True, 'reduce soft constraints if the current correction set is smaller than current core')
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('maxres.pivot_on_correction_set', BOOL, True, 'reduce soft constraints if the current correction set is smaller than current core'),
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('mss.max', UINT, UINT_MAX, 'maximum number of MSS to enumerate')
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))
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