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yap-6.3/packages/bee/glucose-2.2/core/Solver.cc

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bee
2019-04-22 12:15:21 +01:00
/***************************************************************************************[Solver.cc]
Glucose -- Copyright (c) 2009, Gilles Audemard, Laurent Simon
CRIL - Univ. Artois, France
LRI - Univ. Paris Sud, France
Glucose sources are based on MiniSat (see below MiniSat copyrights). Permissions and copyrights of
Glucose are exactly the same as Minisat on which it is based on. (see below).
---------------
Copyright (c) 2003-2006, Niklas Een, Niklas Sorensson
Copyright (c) 2007-2010, Niklas Sorensson
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and
associated documentation files (the "Software"), to deal in the Software without restriction,
including without limitation the rights to use, copy, modify, merge, publish, distribute,
sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or
substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT
NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM,
DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT
OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
**************************************************************************************************/
#include <math.h>
#include "mtl/Sort.h"
#include "core/Solver.h"
#include "core/Constants.h"
using namespace Glucose;
//=================================================================================================
// Options:
static const char* _cat = "CORE";
static const char* _cr = "CORE -- RESTART";
static const char* _cred = "CORE -- REDUCE";
static const char* _cm = "CORE -- MINIMIZE";
static DoubleOption opt_K (_cr, "K", "The constant used to force restart", 0.8, DoubleRange(0, false, 1, false));
static DoubleOption opt_R (_cr, "R", "The constant used to block restart", 1.4, DoubleRange(1, false, 5, false));
static IntOption opt_size_lbd_queue (_cr, "szLBDQueue", "The size of moving average for LBD (restarts)", 50, IntRange(10, INT32_MAX));
static IntOption opt_size_trail_queue (_cr, "szTrailQueue", "The size of moving average for trail (block restarts)", 5000, IntRange(10, INT32_MAX));
static IntOption opt_first_reduce_db (_cred, "firstReduceDB", "The number of conflicts before the first reduce DB", 4000, IntRange(0, INT32_MAX));
static IntOption opt_inc_reduce_db (_cred, "incReduceDB", "Increment for reduce DB", 300, IntRange(0, INT32_MAX));
static IntOption opt_spec_inc_reduce_db (_cred, "specialIncReduceDB", "Special increment for reduce DB", 1000, IntRange(0, INT32_MAX));
static IntOption opt_lb_lbd_frozen_clause (_cred, "minLBDFrozenClause", "Protect clauses if their LBD decrease and is lower than (for one turn)", 30, IntRange(0, INT32_MAX));
static IntOption opt_lb_size_minimzing_clause (_cm, "minSizeMinimizingClause", "The min size required to minimize clause", 30, IntRange(3, INT32_MAX));
static IntOption opt_lb_lbd_minimzing_clause (_cm, "minLBDMinimizingClause", "The min LBD required to minimize clause", 6, IntRange(3, INT32_MAX));
static DoubleOption opt_var_decay (_cat, "var-decay", "The variable activity decay factor", 0.95, DoubleRange(0, false, 1, false));
static DoubleOption opt_clause_decay (_cat, "cla-decay", "The clause activity decay factor", 0.999, DoubleRange(0, false, 1, false));
static DoubleOption opt_random_var_freq (_cat, "rnd-freq", "The frequency with which the decision heuristic tries to choose a random variable", 0, DoubleRange(0, true, 1, true));
static DoubleOption opt_random_seed (_cat, "rnd-seed", "Used by the random variable selection", 91648253, DoubleRange(0, false, HUGE_VAL, false));
static IntOption opt_ccmin_mode (_cat, "ccmin-mode", "Controls conflict clause minimization (0=none, 1=basic, 2=deep)", 2, IntRange(0, 2));
static IntOption opt_phase_saving (_cat, "phase-saving", "Controls the level of phase saving (0=none, 1=limited, 2=full)", 2, IntRange(0, 2));
static BoolOption opt_rnd_init_act (_cat, "rnd-init", "Randomize the initial activity", false);
/*
static IntOption opt_restart_first (_cat, "rfirst", "The base restart interval", 100, IntRange(1, INT32_MAX));
static DoubleOption opt_restart_inc (_cat, "rinc", "Restart interval increase factor", 2, DoubleRange(1, false, HUGE_VAL, false));
*/
static DoubleOption opt_garbage_frac (_cat, "gc-frac", "The fraction of wasted memory allowed before a garbage collection is triggered", 0.20, DoubleRange(0, false, HUGE_VAL, false));
//=================================================================================================
// Constructor/Destructor:
Solver::Solver() :
// Parameters (user settable):
//
verbosity (0)
, K (opt_K)
, R (opt_R)
, sizeLBDQueue (opt_size_lbd_queue)
, sizeTrailQueue (opt_size_trail_queue)
, firstReduceDB (opt_first_reduce_db)
, incReduceDB (opt_inc_reduce_db)
, specialIncReduceDB (opt_spec_inc_reduce_db)
, lbLBDFrozenClause (opt_lb_lbd_frozen_clause)
, lbSizeMinimizingClause (opt_lb_size_minimzing_clause)
, lbLBDMinimizingClause (opt_lb_lbd_minimzing_clause)
, var_decay (opt_var_decay)
, clause_decay (opt_clause_decay)
, random_var_freq (opt_random_var_freq)
, random_seed (opt_random_seed)
, ccmin_mode (opt_ccmin_mode)
, phase_saving (opt_phase_saving)
, rnd_pol (false)
, rnd_init_act (opt_rnd_init_act)
, garbage_frac (opt_garbage_frac)
// Statistics: (formerly in 'SolverStats')
//
, nbRemovedClauses(0),nbReducedClauses(0), nbDL2(0),nbBin(0),nbUn(0) , nbReduceDB(0)
, solves(0), starts(0), decisions(0), rnd_decisions(0), propagations(0), conflicts(0),nbstopsrestarts(0),nbstopsrestartssame(0),lastblockatrestart(0)
, dec_vars(0), clauses_literals(0), learnts_literals(0), max_literals(0), tot_literals(0)
, curRestart(1)
, ok (true)
, cla_inc (1)
, var_inc (1)
, watches (WatcherDeleted(ca))
, watchesBin (WatcherDeleted(ca))
, qhead (0)
, simpDB_assigns (-1)
, simpDB_props (0)
, order_heap (VarOrderLt(activity))
, progress_estimate (0)
, remove_satisfied (true)
// Resource constraints:
//
, conflict_budget (-1)
, propagation_budget (-1)
, asynch_interrupt (false)
{MYFLAG=0;}
Solver::~Solver()
{
}
//=================================================================================================
// Minor methods:
// Creates a new SAT variable in the solver. If 'decision' is cleared, variable will not be
// used as a decision variable (NOTE! This has effects on the meaning of a SATISFIABLE result).
//
Var Solver::newVar(bool sign, bool dvar)
{
int v = nVars();
watches .init(mkLit(v, false));
watches .init(mkLit(v, true ));
watchesBin .init(mkLit(v, false));
watchesBin .init(mkLit(v, true ));
assigns .push(l_Undef);
vardata .push(mkVarData(CRef_Undef, 0));
//activity .push(0);
activity .push(rnd_init_act ? drand(random_seed) * 0.00001 : 0);
seen .push(0);
permDiff .push(0);
polarity .push(sign);
decision .push();
trail .capacity(v+1);
setDecisionVar(v, dvar);
return v;
}
bool Solver::addClause_(vec<Lit>& ps)
{
assert(decisionLevel() == 0);
if (!ok) return false;
// Check if clause is satisfied and remove false/duplicate literals:
sort(ps);
Lit p; int i, j;
for (i = j = 0, p = lit_Undef; i < ps.size(); i++)
if (value(ps[i]) == l_True || ps[i] == ~p)
return true;
else if (value(ps[i]) != l_False && ps[i] != p)
ps[j++] = p = ps[i];
ps.shrink(i - j);
if (ps.size() == 0)
return ok = false;
else if (ps.size() == 1){
uncheckedEnqueue(ps[0]);
return ok = (propagate() == CRef_Undef);
}else{
CRef cr = ca.alloc(ps, false);
clauses.push(cr);
attachClause(cr);
}
return true;
}
void Solver::attachClause(CRef cr) {
const Clause& c = ca[cr];
assert(c.size() > 1);
if(c.size()==2) {
watchesBin[~c[0]].push(Watcher(cr, c[1]));
watchesBin[~c[1]].push(Watcher(cr, c[0]));
} else {
watches[~c[0]].push(Watcher(cr, c[1]));
watches[~c[1]].push(Watcher(cr, c[0]));
}
if (c.learnt()) learnts_literals += c.size();
else clauses_literals += c.size(); }
void Solver::detachClause(CRef cr, bool strict) {
const Clause& c = ca[cr];
assert(c.size() > 1);
if(c.size()==2) {
if (strict){
remove(watchesBin[~c[0]], Watcher(cr, c[1]));
remove(watchesBin[~c[1]], Watcher(cr, c[0]));
}else{
// Lazy detaching: (NOTE! Must clean all watcher lists before garbage collecting this clause)
watchesBin.smudge(~c[0]);
watchesBin.smudge(~c[1]);
}
} else {
if (strict){
remove(watches[~c[0]], Watcher(cr, c[1]));
remove(watches[~c[1]], Watcher(cr, c[0]));
}else{
// Lazy detaching: (NOTE! Must clean all watcher lists before garbage collecting this clause)
watches.smudge(~c[0]);
watches.smudge(~c[1]);
}
}
if (c.learnt()) learnts_literals -= c.size();
else clauses_literals -= c.size(); }
void Solver::removeClause(CRef cr) {
Clause& c = ca[cr];
detachClause(cr);
// Don't leave pointers to free'd memory!
if (locked(c)) vardata[var(c[0])].reason = CRef_Undef;
c.mark(1);
ca.free(cr);
}
bool Solver::satisfied(const Clause& c) const {
for (int i = 0; i < c.size(); i++)
if (value(c[i]) == l_True)
return true;
return false; }
// Revert to the state at given level (keeping all assignment at 'level' but not beyond).
//
void Solver::cancelUntil(int level) {
if (decisionLevel() > level){
for (int c = trail.size()-1; c >= trail_lim[level]; c--){
Var x = var(trail[c]);
assigns [x] = l_Undef;
if (phase_saving > 1 || (phase_saving == 1) && c > trail_lim.last())
polarity[x] = sign(trail[c]);
insertVarOrder(x); }
qhead = trail_lim[level];
trail.shrink(trail.size() - trail_lim[level]);
trail_lim.shrink(trail_lim.size() - level);
} }
//=================================================================================================
// Major methods:
Lit Solver::pickBranchLit()
{
Var next = var_Undef;
// Random decision:
if (drand(random_seed) < random_var_freq && !order_heap.empty()){
next = order_heap[irand(random_seed,order_heap.size())];
if (value(next) == l_Undef && decision[next])
rnd_decisions++; }
// Activity based decision:
while (next == var_Undef || value(next) != l_Undef || !decision[next])
if (order_heap.empty()){
next = var_Undef;
break;
}else
next = order_heap.removeMin();
return next == var_Undef ? lit_Undef : mkLit(next, rnd_pol ? drand(random_seed) < 0.5 : polarity[next]);
}
/*_________________________________________________________________________________________________
|
| analyze : (confl : Clause*) (out_learnt : vec<Lit>&) (out_btlevel : int&) -> [void]
|
| Description:
| Analyze conflict and produce a reason clause.
|
| Pre-conditions:
| * 'out_learnt' is assumed to be cleared.
| * Current decision level must be greater than root level.
|
| Post-conditions:
| * 'out_learnt[0]' is the asserting literal at level 'out_btlevel'.
| * If out_learnt.size() > 1 then 'out_learnt[1]' has the greatest decision level of the
| rest of literals. There may be others from the same level though.
|
|________________________________________________________________________________________________@*/
void Solver::analyze(CRef confl, vec<Lit>& out_learnt, int& out_btlevel,unsigned int &lbd)
{
int pathC = 0;
Lit p = lit_Undef;
// Generate conflict clause:
//
out_learnt.push(); // (leave room for the asserting literal)
int index = trail.size() - 1;
do{
assert(confl != CRef_Undef); // (otherwise should be UIP)
Clause& c = ca[confl];
// Special case for binary clauses
// The first one has to be SAT
if( p != lit_Undef && c.size()==2 && value(c[0])==l_False) {
assert(value(c[1])==l_True);
Lit tmp = c[0];
c[0] = c[1], c[1] = tmp;
}
if (c.learnt())
claBumpActivity(c);
for (int j = (p == lit_Undef) ? 0 : 1; j < c.size(); j++){
Lit q = c[j];
if (!seen[var(q)] && level(var(q)) > 0){
varBumpActivity(var(q));
seen[var(q)] = 1;
if (level(var(q)) >= decisionLevel()) {
pathC++;
#ifdef UPDATEVARACTIVITY
// UPDATEVARACTIVITY trick (see competition'09 companion paper)
if((reason(var(q))!= CRef_Undef) && ca[reason(var(q))].learnt())
lastDecisionLevel.push(q);
#endif
} else {
out_learnt.push(q);
}
}
}
// Select next clause to look at:
while (!seen[var(trail[index--])]);
p = trail[index+1];
confl = reason(var(p));
seen[var(p)] = 0;
pathC--;
}while (pathC > 0);
out_learnt[0] = ~p;
// Simplify conflict clause:
//
int i, j;
out_learnt.copyTo(analyze_toclear);
if (ccmin_mode == 2){
uint32_t abstract_level = 0;
for (i = 1; i < out_learnt.size(); i++)
abstract_level |= abstractLevel(var(out_learnt[i])); // (maintain an abstraction of levels involved in conflict)
for (i = j = 1; i < out_learnt.size(); i++)
if (reason(var(out_learnt[i])) == CRef_Undef || !litRedundant(out_learnt[i], abstract_level))
out_learnt[j++] = out_learnt[i];
}else if (ccmin_mode == 1){
for (i = j = 1; i < out_learnt.size(); i++){
Var x = var(out_learnt[i]);
if (reason(x) == CRef_Undef)
out_learnt[j++] = out_learnt[i];
else{
Clause& c = ca[reason(var(out_learnt[i]))];
for (int k = 1; k < c.size(); k++)
if (!seen[var(c[k])] && level(var(c[k])) > 0){
out_learnt[j++] = out_learnt[i];
break; }
}
}
}else
i = j = out_learnt.size();
max_literals += out_learnt.size();
out_learnt.shrink(i - j);
tot_literals += out_learnt.size();
/* ***************************************
Minimisation with binary clauses of the asserting clause
First of all : we look for small clauses
Then, we reduce clauses with small LBD.
Otherwise, this can be useless
*/
if(out_learnt.size()<=lbSizeMinimizingClause) {
// Find the LBD measure
lbd = 0;
MYFLAG++;
for(int i=0;i<out_learnt.size();i++) {
int l = level(var(out_learnt[i]));
if (permDiff[l] != MYFLAG) {
permDiff[l] = MYFLAG;
lbd++;
}
}
if(lbd<=lbLBDMinimizingClause){
MYFLAG++;
for(int i = 1;i<out_learnt.size();i++) {
permDiff[var(out_learnt[i])] = MYFLAG;
}
vec<Watcher>& wbin = watchesBin[p];
int nb = 0;
for(int k = 0;k<wbin.size();k++) {
Lit imp = wbin[k].blocker;
if(permDiff[var(imp)]==MYFLAG && value(imp)==l_True) {
/* printf("---\n");
printClause(out_learnt);
printf("\n");
printClause(*(wbin[k].clause));printf("\n");
*/
nb++;
permDiff[var(imp)]= MYFLAG-1;
}
}
int l = out_learnt.size()-1;
if(nb>0) {
nbReducedClauses++;
for(int i = 1;i<out_learnt.size()-nb;i++) {
if(permDiff[var(out_learnt[i])]!=MYFLAG) {
Lit p = out_learnt[l];
out_learnt[l] = out_learnt[i];
out_learnt[i] = p;
l--;i--;
}
}
// printClause(out_learnt);
//printf("\n");
out_learnt.shrink(nb);
/*printf("nb=%d\n",nb);
printClause(out_learnt);
printf("\n");
*/
}
}
}
// Find correct backtrack level:
//
if (out_learnt.size() == 1)
out_btlevel = 0;
else{
int max_i = 1;
// Find the first literal assigned at the next-highest level:
for (int i = 2; i < out_learnt.size(); i++)
if (level(var(out_learnt[i])) > level(var(out_learnt[max_i])))
max_i = i;
// Swap-in this literal at index 1:
Lit p = out_learnt[max_i];
out_learnt[max_i] = out_learnt[1];
out_learnt[1] = p;
out_btlevel = level(var(p));
}
// Find the LBD measure
lbd = 0;
MYFLAG++;
for(int i=0;i<out_learnt.size();i++) {
int l = level(var(out_learnt[i]));
if (permDiff[l] != MYFLAG) {
permDiff[l] = MYFLAG;
lbd++;
}
}
#ifdef UPDATEVARACTIVITY
// UPDATEVARACTIVITY trick (see competition'09 companion paper)
if(lastDecisionLevel.size()>0) {
for(int i = 0;i<lastDecisionLevel.size();i++) {
if(ca[reason(var(lastDecisionLevel[i]))].lbd()<lbd)
varBumpActivity(var(lastDecisionLevel[i]));
}
lastDecisionLevel.clear();
}
#endif
for (int j = 0; j < analyze_toclear.size(); j++) seen[var(analyze_toclear[j])] = 0; // ('seen[]' is now cleared)
}
// Check if 'p' can be removed. 'abstract_levels' is used to abort early if the algorithm is
// visiting literals at levels that cannot be removed later.
bool Solver::litRedundant(Lit p, uint32_t abstract_levels)
{
analyze_stack.clear(); analyze_stack.push(p);
int top = analyze_toclear.size();
while (analyze_stack.size() > 0){
assert(reason(var(analyze_stack.last())) != CRef_Undef);
Clause& c = ca[reason(var(analyze_stack.last()))]; analyze_stack.pop();
if(c.size()==2 && value(c[0])==l_False) {
assert(value(c[1])==l_True);
Lit tmp = c[0];
c[0] = c[1], c[1] = tmp;
}
for (int i = 1; i < c.size(); i++){
Lit p = c[i];
if (!seen[var(p)] && level(var(p)) > 0){
if (reason(var(p)) != CRef_Undef && (abstractLevel(var(p)) & abstract_levels) != 0){
seen[var(p)] = 1;
analyze_stack.push(p);
analyze_toclear.push(p);
}else{
for (int j = top; j < analyze_toclear.size(); j++)
seen[var(analyze_toclear[j])] = 0;
analyze_toclear.shrink(analyze_toclear.size() - top);
return false;
}
}
}
}
return true;
}
/*_________________________________________________________________________________________________
|
| analyzeFinal : (p : Lit) -> [void]
|
| Description:
| Specialized analysis procedure to express the final conflict in terms of assumptions.
| Calculates the (possibly empty) set of assumptions that led to the assignment of 'p', and
| stores the result in 'out_conflict'.
|________________________________________________________________________________________________@*/
void Solver::analyzeFinal(Lit p, vec<Lit>& out_conflict)
{
out_conflict.clear();
out_conflict.push(p);
if (decisionLevel() == 0)
return;
seen[var(p)] = 1;
for (int i = trail.size()-1; i >= trail_lim[0]; i--){
Var x = var(trail[i]);
if (seen[x]){
if (reason(x) == CRef_Undef){
assert(level(x) > 0);
out_conflict.push(~trail[i]);
}else{
Clause& c = ca[reason(x)];
// for (int j = 1; j < c.size(); j++) Minisat (glucose 2.0) loop
// Bug in case of assumptions due to special data structures for Binary.
// Many thanks to Sam Bayless (sbayless@cs.ubc.ca) for discover this bug.
for (int j = ((c.size()==2) ? 0:1); j < c.size(); j++)
if (level(var(c[j])) > 0)
seen[var(c[j])] = 1;
}
seen[x] = 0;
}
}
seen[var(p)] = 0;
}
void Solver::uncheckedEnqueue(Lit p, CRef from)
{
assert(value(p) == l_Undef);
assigns[var(p)] = lbool(!sign(p));
vardata[var(p)] = mkVarData(from, decisionLevel());
trail.push_(p);
}
/*_________________________________________________________________________________________________
|
| propagate : [void] -> [Clause*]
|
| Description:
| Propagates all enqueued facts. If a conflict arises, the conflicting clause is returned,
| otherwise CRef_Undef.
|
| Post-conditions:
| * the propagation queue is empty, even if there was a conflict.
|________________________________________________________________________________________________@*/
CRef Solver::propagate()
{
CRef confl = CRef_Undef;
int num_props = 0;
watches.cleanAll();
watchesBin.cleanAll();
while (qhead < trail.size()){
Lit p = trail[qhead++]; // 'p' is enqueued fact to propagate.
vec<Watcher>& ws = watches[p];
Watcher *i, *j, *end;
num_props++;
// First, Propagate binary clauses
vec<Watcher>& wbin = watchesBin[p];
for(int k = 0;k<wbin.size();k++) {
Lit imp = wbin[k].blocker;
if(value(imp) == l_False) {
return wbin[k].cref;
}
if(value(imp) == l_Undef) {
//printLit(p);printf(" ");printClause(wbin[k].cref);printf("-> ");printLit(imp);printf("\n");
uncheckedEnqueue(imp,wbin[k].cref);
}
}
for (i = j = (Watcher*)ws, end = i + ws.size(); i != end;){
// Try to avoid inspecting the clause:
Lit blocker = i->blocker;
if (value(blocker) == l_True){
*j++ = *i++; continue; }
// Make sure the false literal is data[1]:
CRef cr = i->cref;
Clause& c = ca[cr];
Lit false_lit = ~p;
if (c[0] == false_lit)
c[0] = c[1], c[1] = false_lit;
assert(c[1] == false_lit);
i++;
// If 0th watch is true, then clause is already satisfied.
Lit first = c[0];
Watcher w = Watcher(cr, first);
if (first != blocker && value(first) == l_True){
*j++ = w; continue; }
// Look for new watch:
for (int k = 2; k < c.size(); k++)
if (value(c[k]) != l_False){
c[1] = c[k]; c[k] = false_lit;
watches[~c[1]].push(w);
goto NextClause; }
// Did not find watch -- clause is unit under assignment:
*j++ = w;
if (value(first) == l_False){
confl = cr;
qhead = trail.size();
// Copy the remaining watches:
while (i < end)
*j++ = *i++;
}else {
uncheckedEnqueue(first, cr);
#ifdef DYNAMICNBLEVEL
// DYNAMIC NBLEVEL trick (see competition'09 companion paper)
if(c.learnt() && c.lbd()>2) {
MYFLAG++;
unsigned int nblevels =0;
for(int i=0;i<c.size();i++) {
int l = level(var(c[i]));
if (permDiff[l] != MYFLAG) {
permDiff[l] = MYFLAG;
nblevels++;
}
}
if(nblevels+1<c.lbd() ) { // improve the LBD
if(c.lbd()<=lbLBDFrozenClause) {
c.setCanBeDel(false);
}
// seems to be interesting : keep it for the next round
c.setLBD(nblevels); // Update it
}
}
#endif
}
NextClause:;
}
ws.shrink(i - j);
}
propagations += num_props;
simpDB_props -= num_props;
return confl;
}
/*_________________________________________________________________________________________________
|
| reduceDB : () -> [void]
|
| Description:
| Remove half of the learnt clauses, minus the clauses locked by the current assignment. Locked
| clauses are clauses that are reason to some assignment. Binary clauses are never removed.
|________________________________________________________________________________________________@*/
struct reduceDB_lt {
ClauseAllocator& ca;
reduceDB_lt(ClauseAllocator& ca_) : ca(ca_) {}
bool operator () (CRef x, CRef y) {
// Main criteria... Like in MiniSat we keep all binary clauses
if(ca[x].size()> 2 && ca[y].size()==2) return 1;
if(ca[y].size()>2 && ca[x].size()==2) return 0;
if(ca[x].size()==2 && ca[y].size()==2) return 0;
// Second one based on literal block distance
if(ca[x].lbd()> ca[y].lbd()) return 1;
if(ca[x].lbd()< ca[y].lbd()) return 0;
// Finally we can use old activity or size, we choose the last one
return ca[x].activity() < ca[y].activity();
//return x->size() < y->size();
//return ca[x].size() > 2 && (ca[y].size() == 2 || ca[x].activity() < ca[y].activity()); }
}
};
void Solver::reduceDB()
{
int i, j;
nbReduceDB++;
sort(learnts, reduceDB_lt(ca));
// We have a lot of "good" clauses, it is difficult to compare them. Keep more !
if(ca[learnts[learnts.size() / RATIOREMOVECLAUSES]].lbd()<=3) nbclausesbeforereduce +=specialIncReduceDB;
// Useless :-)
if(ca[learnts.last()].lbd()<=5) nbclausesbeforereduce +=specialIncReduceDB;
// Don't delete binary or locked clauses. From the rest, delete clauses from the first half
// Keep clauses which seem to be usefull (their lbd was reduce during this sequence)
int limit = learnts.size() / 2;
for (i = j = 0; i < learnts.size(); i++){
Clause& c = ca[learnts[i]];
if (c.lbd()>2 && c.size() > 2 && c.canBeDel() && !locked(c) && (i < limit)) {
removeClause(learnts[i]);
nbRemovedClauses++;
}
else {
if(!c.canBeDel()) limit++; //we keep c, so we can delete an other clause
c.setCanBeDel(true); // At the next step, c can be delete
learnts[j++] = learnts[i];
}
}
learnts.shrink(i - j);
checkGarbage();
}
void Solver::removeSatisfied(vec<CRef>& cs)
{
int i, j;
for (i = j = 0; i < cs.size(); i++){
Clause& c = ca[cs[i]];
if (c.size()>=2 && satisfied(c)) // A bug if we remove size ==2, We need to correct it, but later.
removeClause(cs[i]);
else
cs[j++] = cs[i];
}
cs.shrink(i - j);
}
void Solver::rebuildOrderHeap()
{
vec<Var> vs;
for (Var v = 0; v < nVars(); v++)
if (decision[v] && value(v) == l_Undef)
vs.push(v);
order_heap.build(vs);
}
/*_________________________________________________________________________________________________
|
| simplify : [void] -> [bool]
|
| Description:
| Simplify the clause database according to the current top-level assigment. Currently, the only
| thing done here is the removal of satisfied clauses, but more things can be put here.
|________________________________________________________________________________________________@*/
bool Solver::simplify()
{
assert(decisionLevel() == 0);
if (!ok || propagate() != CRef_Undef)
return ok = false;
if (nAssigns() == simpDB_assigns || (simpDB_props > 0))
return true;
// Remove satisfied clauses:
removeSatisfied(learnts);
if (remove_satisfied) // Can be turned off.
removeSatisfied(clauses);
checkGarbage();
rebuildOrderHeap();
simpDB_assigns = nAssigns();
simpDB_props = clauses_literals + learnts_literals; // (shouldn't depend on stats really, but it will do for now)
return true;
}
/*_________________________________________________________________________________________________
|
| search : (nof_conflicts : int) (params : const SearchParams&) -> [lbool]
|
| Description:
| Search for a model the specified number of conflicts.
| NOTE! Use negative value for 'nof_conflicts' indicate infinity.
|
| Output:
| 'l_True' if a partial assigment that is consistent with respect to the clauseset is found. If
| all variables are decision variables, this means that the clause set is satisfiable. 'l_False'
| if the clause set is unsatisfiable. 'l_Undef' if the bound on number of conflicts is reached.
|________________________________________________________________________________________________@*/
lbool Solver::search(int nof_conflicts)
{
assert(ok);
int backtrack_level;
int conflictC = 0;
vec<Lit> learnt_clause;
unsigned int nblevels;
bool blocked=false;
starts++;
for (;;){
CRef confl = propagate();
if (confl != CRef_Undef){
// CONFLICT
conflicts++; conflictC++;
if (verbosity >= 1 && conflicts%verbEveryConflicts==0){
printf("c | %8d %7d %5d | %7d %8d %8d | %5d %8d %6d %8d | %6.3f %% |\n",
(int)starts,(int)nbstopsrestarts, (int)(conflicts/starts),
(int)dec_vars - (trail_lim.size() == 0 ? trail.size() : trail_lim[0]), nClauses(), (int)clauses_literals,
(int)nbReduceDB, nLearnts(), (int)nbDL2,(int)nbRemovedClauses, progressEstimate()*100);
}
if (decisionLevel() == 0) {
return l_False;
}
trailQueue.push(trail.size());
if( conflicts>LOWER_BOUND_FOR_BLOCKING_RESTART && lbdQueue.isvalid() && trail.size()>R*trailQueue.getavg()) {
lbdQueue.fastclear();
nbstopsrestarts++;
if(!blocked) {lastblockatrestart=starts;nbstopsrestartssame++;blocked=true;}
}
learnt_clause.clear();
analyze(confl, learnt_clause, backtrack_level,nblevels);
lbdQueue.push(nblevels);
sumLBD += nblevels;
cancelUntil(backtrack_level);
if (learnt_clause.size() == 1){
uncheckedEnqueue(learnt_clause[0]);nbUn++;
}else{
CRef cr = ca.alloc(learnt_clause, true);
ca[cr].setLBD(nblevels);
if(nblevels<=2) nbDL2++; // stats
if(ca[cr].size()==2) nbBin++; // stats
learnts.push(cr);
attachClause(cr);
claBumpActivity(ca[cr]);
uncheckedEnqueue(learnt_clause[0], cr);
}
varDecayActivity();
claDecayActivity();
}else{
// Our dynamic restart, see the SAT09 competition compagnion paper
if (
( lbdQueue.isvalid() && ((lbdQueue.getavg()*K) > (sumLBD / conflicts)))) {
lbdQueue.fastclear();
progress_estimate = progressEstimate();
cancelUntil(0);
return l_Undef; }
// Simplify the set of problem clauses:
if (decisionLevel() == 0 && !simplify()) {
if (verbosity >= 1)
printf("c last restart ## conflicts : %d %d \n",conflictC,decisionLevel());
return l_False;
}
// Perform clause database reduction !
if(conflicts>=curRestart* nbclausesbeforereduce)
{
assert(learnts.size()>0);
curRestart = (conflicts/ nbclausesbeforereduce)+1;
reduceDB();
nbclausesbeforereduce += incReduceDB;
}
Lit next = lit_Undef;
while (decisionLevel() < assumptions.size()){
// Perform user provided assumption:
Lit p = assumptions[decisionLevel()];
if (value(p) == l_True){
// Dummy decision level:
newDecisionLevel();
}else if (value(p) == l_False){
analyzeFinal(~p, conflict);
return l_False;
}else{
next = p;
break;
}
}
if (next == lit_Undef){
// New variable decision:
decisions++;
next = pickBranchLit();
if (next == lit_Undef) {
if (verbosity >= 1)
printf("c last restart ## conflicts : %d %d \n",conflictC,decisionLevel());
// Model found:
return l_True;
}
}
// Increase decision level and enqueue 'next'
newDecisionLevel();
uncheckedEnqueue(next);
}
}
}
double Solver::progressEstimate() const
{
double progress = 0;
double F = 1.0 / nVars();
for (int i = 0; i <= decisionLevel(); i++){
int beg = i == 0 ? 0 : trail_lim[i - 1];
int end = i == decisionLevel() ? trail.size() : trail_lim[i];
progress += pow(F, i) * (end - beg);
}
return progress / nVars();
}
// NOTE: assumptions passed in member-variable 'assumptions'.
lbool Solver::solve_()
{
model.clear();
conflict.clear();
if (!ok) return l_False;
lbdQueue.initSize(sizeLBDQueue);
trailQueue.initSize(sizeTrailQueue);
sumLBD = 0;
solves++;
lbool status = l_Undef;
nbclausesbeforereduce = firstReduceDB;
if(verbosity>=1) {
printf("c ========================================[ MAGIC CONSTANTS ]==============================================\n");
printf("c | Constants are supposed to work well together :-) |\n");
printf("c | however, if you find better choices, please let us known... |\n");
printf("c |-------------------------------------------------------------------------------------------------------|\n");
printf("c | | | |\n");
printf("c | - Restarts: | - Reduce Clause DB: | - Minimize Asserting: |\n");
printf("c | * LBD Queue : %6d | * First : %6d | * size < %3d |\n",lbdQueue.maxSize(),firstReduceDB,lbSizeMinimizingClause);
printf("c | * Trail Queue : %6d | * Inc : %6d | * lbd < %3d |\n",trailQueue.maxSize(),incReduceDB,lbLBDMinimizingClause);
printf("c | * K : %6.2f | * Special : %6d | |\n",K,specialIncReduceDB);
printf("c | * R : %6.2f | * Protected : (lbd)< %2d | |\n",R,lbLBDFrozenClause);
printf("c | | | |\n");
printf("c ==================================[ Search Statistics (every %6d conflicts) ]=========================\n",verbEveryConflicts);
printf("c | |\n");
printf("c | RESTARTS | ORIGINAL | LEARNT | Progress |\n");
printf("c | NB Blocked Avg Cfc | Vars Clauses Literals | Red Learnts LBD2 Removed | |\n");
printf("c =========================================================================================================\n");
}
// Search:
int curr_restarts = 0;
while (status == l_Undef){
status = search(0); // the parameter is useless in glucose, kept to allow modifications
if (!withinBudget()) break;
curr_restarts++;
}
if (verbosity >= 1)
printf("c =========================================================================================================\n");
if (status == l_True){
// Extend & copy model:
model.growTo(nVars());
for (int i = 0; i < nVars(); i++) model[i] = value(i);
}else if (status == l_False && conflict.size() == 0)
ok = false;
cancelUntil(0);
return status;
}
//=================================================================================================
// Writing CNF to DIMACS:
//
// FIXME: this needs to be rewritten completely.
static Var mapVar(Var x, vec<Var>& map, Var& max)
{
if (map.size() <= x || map[x] == -1){
map.growTo(x+1, -1);
map[x] = max++;
}
return map[x];
}
void Solver::toDimacs(FILE* f, Clause& c, vec<Var>& map, Var& max)
{
if (satisfied(c)) return;
for (int i = 0; i < c.size(); i++)
if (value(c[i]) != l_False)
fprintf(f, "%s%d ", sign(c[i]) ? "-" : "", mapVar(var(c[i]), map, max)+1);
fprintf(f, "0\n");
}
void Solver::toDimacs(const char *file, const vec<Lit>& assumps)
{
FILE* f = fopen(file, "wr");
if (f == NULL)
fprintf(stderr, "could not open file %s\n", file), exit(1);
toDimacs(f, assumps);
fclose(f);
}
void Solver::toDimacs(FILE* f, const vec<Lit>& assumps)
{
// Handle case when solver is in contradictory state:
if (!ok){
fprintf(f, "p cnf 1 2\n1 0\n-1 0\n");
return; }
vec<Var> map; Var max = 0;
// Cannot use removeClauses here because it is not safe
// to deallocate them at this point. Could be improved.
int cnt = 0;
for (int i = 0; i < clauses.size(); i++)
if (!satisfied(ca[clauses[i]]))
cnt++;
for (int i = 0; i < clauses.size(); i++)
if (!satisfied(ca[clauses[i]])){
Clause& c = ca[clauses[i]];
for (int j = 0; j < c.size(); j++)
if (value(c[j]) != l_False)
mapVar(var(c[j]), map, max);
}
// Assumptions are added as unit clauses:
cnt += assumptions.size();
fprintf(f, "p cnf %d %d\n", max, cnt);
for (int i = 0; i < assumptions.size(); i++){
assert(value(assumptions[i]) != l_False);
fprintf(f, "%s%d 0\n", sign(assumptions[i]) ? "-" : "", mapVar(var(assumptions[i]), map, max)+1);
}
for (int i = 0; i < clauses.size(); i++)
toDimacs(f, ca[clauses[i]], map, max);
if (verbosity > 0)
printf("Wrote %d clauses with %d variables.\n", cnt, max);
}
//=================================================================================================
// Garbage Collection methods:
void Solver::relocAll(ClauseAllocator& to)
{
// All watchers:
//
// for (int i = 0; i < watches.size(); i++)
watches.cleanAll();
watchesBin.cleanAll();
for (int v = 0; v < nVars(); v++)
for (int s = 0; s < 2; s++){
Lit p = mkLit(v, s);
// printf(" >>> RELOCING: %s%d\n", sign(p)?"-":"", var(p)+1);
vec<Watcher>& ws = watches[p];
for (int j = 0; j < ws.size(); j++)
ca.reloc(ws[j].cref, to);
vec<Watcher>& ws2 = watchesBin[p];
for (int j = 0; j < ws2.size(); j++)
ca.reloc(ws2[j].cref, to);
}
// All reasons:
//
for (int i = 0; i < trail.size(); i++){
Var v = var(trail[i]);
if (reason(v) != CRef_Undef && (ca[reason(v)].reloced() || locked(ca[reason(v)])))
ca.reloc(vardata[v].reason, to);
}
// All learnt:
//
for (int i = 0; i < learnts.size(); i++)
ca.reloc(learnts[i], to);
// All original:
//
for (int i = 0; i < clauses.size(); i++)
ca.reloc(clauses[i], to);
}
void Solver::garbageCollect()
{
// Initialize the next region to a size corresponding to the estimated utilization degree. This
// is not precise but should avoid some unnecessary reallocations for the new region:
ClauseAllocator to(ca.size() - ca.wasted());
relocAll(to);
if (verbosity >= 2)
printf("| Garbage collection: %12d bytes => %12d bytes |\n",
ca.size()*ClauseAllocator::Unit_Size, to.size()*ClauseAllocator::Unit_Size);
to.moveTo(ca);
}
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