Something went wrong. Try again.
This repository has no description
Something went wrong. Try again.
26 kB · 832 lines
C++
at develop
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263264265266267268269270271272273274275276277278279280281282283284285286287288289290291292293294295296297298299300301302303304305306307308309310311312313314315316317318319320321322323324325326327328329330331332333334335336337338339340341342343344345346347348349350351352353354355356357358359360361362363364365366367368369370371372373374375376377378379380381382383384385386387388389390391392393394395396397398399400401402403404405406407408409410411412413414415416417418419420421422423424425426427428429430431432433434435436437438439440441442443444445446447448449450451452453454455456457458459460461462463464465466467468469470471472473474475476477478479480481482483484485486487488489490491492493494495496497498499500501502503504505506507508509510511512513514515516517518519520521522523524525526527528529530531532533534535536537538539540541542543544545546547548549550551552553554555556557558559560561562563564565566567568569570571572573574575576577578579580581582583584585586587588589590591592593594595596597598599600601602603604605606607608609610611612613614615616617618619620621622623624625626627628629630631632633634635636637638639640641642643644645646647648649650651652653654655656657658659660661662663664665666667668669670671672673674675676677678679680681682683684685686687688689690691692693694695696697698699700701702703704705706707708709710711712713714715716717718719720721722723724725726727728729730731732733734735736737738739740741742743744745746747748749750751752753754755756757758759760761762763764765766767768769770771772773774775776777778779780781782783784785786787788789790791792793794795796797798799800801802803804805806807808809810811812813814815816817818819820821822823824825826827828829830831832833/* -*- mode: C++; c-basic-offset: 2; indent-tabs-mode: nil -*- *//* * Main authors: * Patrick Pekczynski <pekczynski@ps.uni-sb.de> * * Contributing authors: * Christian Schulte <schulte@gecode.org> * Guido Tack <tack@gecode.org> * * Copyright: * Patrick Pekczynski, 2004/2005 * Christian Schulte, 2009 * Guido Tack, 2009 * * This file is part of Gecode, the generic constraint * development environment: * http://www.gecode.org * * 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. * */
namespace Gecode { namespace Int { namespace GCC {
template<class Card> forceinline Bnd<Card>:: Bnd(Home home, ViewArray<IntView>& x0, ViewArray<Card>& k0, bool cf, bool nolbc) : Propagator(home), x(x0), y(home, x0), k(k0), card_fixed(cf), skip_lbc(nolbc) { y.subscribe(home, *this, PC_INT_BND); k.subscribe(home, *this, PC_INT_BND); }
template<class Card> forceinline Bnd<Card>:: Bnd(Space& home, Bnd<Card>& p) : Propagator(home, p), card_fixed(p.card_fixed), skip_lbc(p.skip_lbc) { x.update(home, p.x); y.update(home, p.y); k.update(home, p.k); }
template<class Card> forceinline size_t Bnd<Card>::dispose(Space& home) { y.cancel(home,*this, PC_INT_BND); k.cancel(home,*this, PC_INT_BND); (void) Propagator::dispose(home); return sizeof(*this); }
template<class Card> Actor* Bnd<Card>::copy(Space& home) { return new (home) Bnd<Card>(home,*this); }
template<class Card> PropCost Bnd<Card>::cost(const Space&, const ModEventDelta& med) const { int n_k = Card::propagate ? k.size() : 0; if (IntView::me(med) == ME_INT_VAL) return PropCost::linear(PropCost::LO, y.size() + n_k); else return PropCost::quadratic(PropCost::LO, x.size() + n_k); }
template<class Card> void Bnd<Card>::reschedule(Space& home) { y.reschedule(home, *this, PC_INT_BND); k.reschedule(home, *this, PC_INT_BND); }
template<class Card> forceinline ExecStatus Bnd<Card>::lbc(Space& home, int& nb, HallInfo hall[], Rank rank[], int mu[], int nu[]) { int n = x.size();
/* * Let I(S) denote the number of variables whose domain intersects * the set S and C(S) the number of variables whose domain is containded * in S. Let further min_cap(S) be the minimal number of variables * that must be assigned to values, that is * min_cap(S) is the sum over all l[i] for a value v_i that is an * element of S. * * A failure set is a set F if * I(F) < min_cap(F) * An unstable set is a set U if * I(U) = min_cap(U) * A stable set is a set S if * C(S) > min_cap(S) and S intersetcs nor * any failure set nor any unstable set * forall unstable and failure sets * * failure sets determine the satisfiability of the LBC * unstable sets have to be pruned * stable set do not have to be pruned * * hall[].ps ~ stores the unstable * sets that have to be pruned * hall[].s ~ stores sets that must not be pruned * hall[].h ~ contains stable and unstable sets * hall[].d ~ contains the difference between interval bounds, i.e. * the minimal capacity of the interval * hall[].t ~ contains the critical capacity pointer, pointing to the * values */
// LBC lower bounds
int i = 0; int j = 0; int w = 0; int z = 0; int v = 0;
//initialization of the tree structure int rightmost = nb + 1; // rightmost accesible value in bounds int bsize = nb + 2; w = rightmost;
// test // unused but uninitialized hall[0].d = 0; hall[0].s = 0; hall[0].ps = 0;
for (i = bsize; --i; ) { // i must not be zero int pred = i - 1; hall[i].s = pred; hall[i].ps = pred; hall[i].d = lps.sumup(hall[pred].bounds, hall[i].bounds - 1);
/* Let [hall[i].bounds,hall[i-1].bounds]=:I * If the capacity is zero => min_cap(I) = 0 * => I cannot be a failure set * => I is an unstable set */ if (hall[i].d == 0) { hall[pred].h = w; } else { hall[w].h = pred; w = pred; } }
w = rightmost; for (i = bsize; i--; ) { // i can be zero hall[i].t = i - 1; if (hall[i].d == 0) { hall[i].t = w; } else { hall[w].t = i; w = i; } }
/* * The algorithm assigns to each value v in bounds * empty buckets corresponding to the minimal capacity l[i] to be * filled for v. (the buckets correspond to hall[].d containing the * difference between the interval bounds) Processing it * searches for the smallest value v in dom(x_i) that has an * empty bucket, i.e. if all buckets are filled it is guaranteed * that there are at least l[i] variables that will be * instantiated to v. Since the buckets are initially empty, * they are considered as FAILURE SETS */
for (i = 0; i < n; i++) { // visit intervals in increasing max order int x0 = rank[mu[i]].min; int y = rank[mu[i]].max; int succ = x0 + 1; z = pathmax_t(hall, succ); j = hall[z].t;
/* * POTENTIALLY STABLE SET: * z \neq succ \Leftrigharrow z>succ, i.e. * min(D_{\mu(i)}) is guaranteed to occur min(K_i) times * \Rightarrow [x0, min(y,z)] is potentially stable */
if (z != succ) { w = pathmax_ps(hall, succ); v = hall[w].ps; pathset_ps(hall, succ, w, w); w = std::min(y, z); pathset_ps(hall, hall[w].ps, v, w); hall[w].ps = v; }
/* * STABLE SET: * being stable implies being potentially stable, i.e. * [hall[y].ps, hall[y].bounds-1] is the largest stable subset of * [hall[j].bounds, hall[y].bounds-1]. */
if (hall[z].d <= lps.sumup(hall[y].bounds, hall[z].bounds - 1)) { w = pathmax_s(hall, hall[y].ps); pathset_s(hall, hall[y].ps, w, w); // Path compression v = hall[w].s; pathset_s(hall, hall[y].s, v, y); hall[y].s = v; } else { /* * FAILURE SET: * If the considered interval [x0,y] is neither POTENTIALLY STABLE * nor STABLE there are still buckets that can be filled, * therefore d can be decreased. If d equals zero the intervals * minimum capacity is met and thepath can be compressed to the * next value having an empty bucket. * see DOMINATION in "ubc" */ if (--hall[z].d == 0) { hall[z].t = z + 1; z = pathmax_t(hall, hall[z].t); hall[z].t = j; }
/* * FINDING NEW LOWER BOUND: * If the lower bound belongs to an unstable or a stable set, * remind the new value we might assigned to the lower bound * in case the variable doesn't belong to a stable set. */ if (hall[x0].h > x0) { hall[i].newBound = pathmax_h(hall, x0); w = hall[i].newBound; pathset_h(hall, x0, w, w); // path compression } else { // Do not shrink the variable: take old min as new min hall[i].newBound = x0; }
/* UNSTABLE SET * If an unstable set is discovered * the difference between the interval bounds is equal to the * number of variables whose domain intersect the interval * (see ZEROTEST in "gcc") */ // CLEARLY THIS WAS NOT STABLE == UNSTABLE if (hall[z].d == lps.sumup(hall[y].bounds, hall[z].bounds - 1)) { if (hall[y].h > y) /* * y is not the end of the potentially stable set * thus ensure that the potentially stable superset is marked */ y = hall[y].h; // Equivalent to pathmax since the path is fully compressed pathset_h(hall, hall[y].h, j-1, y); // mark the new unstable set [j,y] hall[y].h = j-1; } } pathset_t(hall, succ, z, z); // path compression }
/* If there is a FAILURE SET left the minimum occurences of the values * are not guaranteed. In order to satisfy the LBC the last value * in the stable and unstable datastructure hall[].h must point to * the sentinel at the beginning of bounds. */ if (hall[nb].h != 0) return ES_FAILED;
// Perform path compression over all elements in // the stable interval data structure. This data // structure will no longer be modified and will be // accessed n or 2n times. Therefore, we can afford // a linear time compression. for (i = bsize; --i;) if (hall[i].s > i) hall[i].s = w; else w = i;
/* * UPDATING LOWER BOUND: * For all variables that are not a subset of a stable set, * shrink the lower bound, i.e. forall stable sets S we have: * x0 < S_min <= y <=S_max or S_min <= x0 <= S_max < y * that is [x0,y] is NOT a proper subset of any stable set S */ for (i = n; i--; ) { int x0 = rank[mu[i]].min; int y = rank[mu[i]].max; // update only those variables that are not contained in a stable set if ((hall[x0].s <= x0) || (y > hall[x0].s)) { // still have to check this out, how skipping works (consider dominated indices) int m = lps.skipNonNullElementsRight(hall[hall[i].newBound].bounds); GECODE_ME_CHECK(x[mu[i]].gq(home, m)); } }
// LBC narrow upper bounds w = 0; for (i = 0; i <= nb; i++) { hall[i].d = lps.sumup(hall[i].bounds, hall[i + 1].bounds - 1); if (hall[i].d == 0) { hall[i].t = w; } else { hall[w].t = i; w = i; } } hall[w].t = i;
w = 0; for (i = 1; i <= nb; i++) if (hall[i - 1].d == 0) { hall[i].h = w; } else { hall[w].h = i; w = i; } hall[w].h = i;
for (i = n; i--; ) { // visit intervals in decreasing min order // i.e. minsorted from right to left int x0 = rank[nu[i]].max; int y = rank[nu[i]].min; int pred = x0 - 1; // predecessor of x0 in the indices z = pathmin_t(hall, pred); j = hall[z].t;
/* If the variable is not in a discovered stable set * (see above condition for STABLE SET) */ if (hall[z].d > lps.sumup(hall[z].bounds, hall[y].bounds - 1)) { // FAILURE SET if (--hall[z].d == 0) { hall[z].t = z - 1; z = pathmin_t(hall, hall[z].t); hall[z].t = j; } // FINDING NEW UPPER BOUND if (hall[x0].h < x0) { w = pathmin_h(hall, hall[x0].h); hall[i].newBound = w; pathset_h(hall, x0, w, w); // path compression } else { hall[i].newBound = x0; } // UNSTABLE SET if (hall[z].d == lps.sumup(hall[z].bounds, hall[y].bounds - 1)) { if (hall[y].h < y) { y = hall[y].h; } int succj = j + 1; // mark new unstable set [y,j] pathset_h(hall, hall[y].h, succj, y); hall[y].h = succj; } } pathset_t(hall, pred, z, z); }
// UPDATING UPPER BOUND for (i = n; i--; ) { int x0 = rank[nu[i]].min; int y = rank[nu[i]].max; if ((hall[x0].s <= x0) || (y > hall[x0].s)) { int m = lps.skipNonNullElementsLeft(hall[hall[i].newBound].bounds - 1); GECODE_ME_CHECK(x[nu[i]].lq(home, m)); } } return ES_OK; }
template<class Card> forceinline ExecStatus Bnd<Card>::ubc(Space& home, int& nb, HallInfo hall[], Rank rank[], int mu[], int nu[]) { int rightmost = nb + 1; // rightmost accesible value in bounds int bsize = nb + 2; // number of unique bounds including sentinels
//Narrow lower bounds (UBC)
/* * Initializing tree structure with the values from bounds * and the interval capacities of neighboured values * from left to right */
hall[0].h = 0; hall[0].t = 0; hall[0].d = 0;
for (int i = bsize; --i; ) { hall[i].h = hall[i].t = i-1; hall[i].d = ups.sumup(hall[i-1].bounds, hall[i].bounds - 1); }
int n = x.size();
for (int i = 0; i < n; i++) { // visit intervals in increasing max order int x0 = rank[mu[i]].min; int succ = x0 + 1; int y = rank[mu[i]].max; int z = pathmax_t(hall, succ); int j = hall[z].t;
/* DOMINATION: * v^i_j denotes * unused values in the current interval. If the difference d * between to critical capacities v^i_j and v^i_z * is equal to zero, j dominates z * * i.e. [hall[l].bounds, hall[nb+1].bounds] is not left-maximal and * [hall[j].bounds, hall[l].bounds] is a Hall set iff * [hall[j].bounds, hall[l].bounds] processing a variable x_i uses up a value in the interval * [hall[z].bounds,hall[z+1].bounds] according to the intervals * capacity. Therefore, if d = 0 * the considered value has already been used by processed variables * m-times, where m = u[i] for value v_i. Since this value must not * be reconsidered the path can be compressed */ if (--hall[z].d == 0) { hall[z].t = z + 1; z = pathmax_t(hall, hall[z].t); if (z >= bsize) z--; hall[z].t = j; } pathset_t(hall, succ, z, z); // path compression
/* NEGATIVE CAPACITY: * A negative capacity results in a failure.Since a * negative capacity signals that the number of variables * whose domain is contained in the set S is larger than * the maximum capacity of S => UBC is not satisfiable, * i.e. there are more variables than values to instantiate them */ if (hall[z].d < ups.sumup(hall[y].bounds, hall[z].bounds - 1)) return ES_FAILED;
/* UPDATING LOWER BOUND: * If the lower bound min_i lies inside a Hall interval [a,b] * i.e. a <= min_i <=b <= max_i * min_i is set to min_i := b+1 */ if (hall[x0].h > x0) { int w = pathmax_h(hall, hall[x0].h); int m = hall[w].bounds; GECODE_ME_CHECK(x[mu[i]].gq(home, m)); pathset_h(hall, x0, w, w); // path compression }
/* ZEROTEST: * (using the difference between capacity pointers) * zero capacity => the difference between critical capacity * pointers is equal to the maximum capacity of the interval,i.e. * the number of variables whose domain is contained in the * interval is equal to the sum over all u[i] for a value v_i that * lies in the Hall-Intervall which can also be thought of as a * Hall-Set * * ZeroTestLemma: Let k and l be succesive critical indices. * v^i_k=0 => v^i_k = max_i+1-l+d * <=> v^i_k = y + 1 - z + d * <=> d = z-1-y * if this equation holds the interval [j,z-1] is a hall intervall */
if (hall[z].d == ups.sumup(hall[y].bounds, hall[z].bounds - 1)) { /* *mark hall interval [j,z-1] * hall pointers form a path to the upper bound of the interval */ int predj = j - 1; pathset_h(hall, hall[y].h, predj, y); hall[y].h = predj; } }
/* Narrow upper bounds (UBC) * symmetric to the narrowing of the lower bounds */ for (int i = 0; i < rightmost; i++) { hall[i].h = hall[i].t = i+1; hall[i].d = ups.sumup(hall[i].bounds, hall[i+1].bounds - 1); }
for (int i = n; i--; ) { // visit intervals in decreasing min order int x0 = rank[nu[i]].max; int pred = x0 - 1; int y = rank[nu[i]].min; int z = pathmin_t(hall, pred); int j = hall[z].t;
// DOMINATION: if (--hall[z].d == 0) { hall[z].t = z - 1; z = pathmin_t(hall, hall[z].t); hall[z].t = j; } pathset_t(hall, pred, z, z);
// NEGATIVE CAPACITY: if (hall[z].d < ups.sumup(hall[z].bounds,hall[y].bounds-1)) return ES_FAILED;
/* UPDATING UPPER BOUND: * If the upper bound max_i lies inside a Hall interval [a,b] * i.e. min_i <= a <= max_i < b * max_i is set to max_i := a-1 */ if (hall[x0].h < x0) { int w = pathmin_h(hall, hall[x0].h); int m = hall[w].bounds - 1; GECODE_ME_CHECK(x[nu[i]].lq(home, m)); pathset_h(hall, x0, w, w); }
// ZEROTEST if (hall[z].d == ups.sumup(hall[z].bounds, hall[y].bounds - 1)) { //mark hall interval [y,j] pathset_h(hall, hall[y].h, j+1, y); hall[y].h = j+1; } } return ES_OK; }
template<class Card> ExecStatus Bnd<Card>::pruneCards(Space& home) { // Remove all values with 0 max occurrence // and remove corresponding occurrence variables from k
// The number of zeroes int n_z = 0; for (int i=k.size(); i--;) if (k[i].max() == 0) n_z++;
if (n_z > 0) { Region r; int* z = r.alloc<int>(n_z); n_z = 0; int n_k = 0; for (int i=0; i<k.size(); i++) if (k[i].max() == 0) { z[n_z++] = k[i].card(); } else { k[n_k++] = k[i]; } k.size(n_k); Support::quicksort(z,n_z); for (int i=x.size(); i--;) { Iter::Values::Array zi(z,n_z); GECODE_ME_CHECK(x[i].minus_v(home,zi,false)); } lps.reinit(); ups.reinit(); } return ES_OK; }
template<class Card> ExecStatus Bnd<Card>::propagate(Space& home, const ModEventDelta& med) { if (IntView::me(med) == ME_INT_VAL) { GECODE_ES_CHECK(prop_val<Card>(home,*this,y,k)); return home.ES_NOFIX_PARTIAL(*this,IntView::med(ME_INT_BND)); }
if (Card::propagate) GECODE_ES_CHECK(pruneCards(home));
Region r; int* count = r.alloc<int>(k.size());
for (int i = k.size(); i--; ) count[i] = 0; bool all_assigned = true; int noa = 0; for (int i = x.size(); i--; ) { if (x[i].assigned()) { noa++; int idx; // reduction is essential for order on value nodes in dom // hence introduce test for failed lookup if (!lookupValue(k,x[i].val(),idx)) return ES_FAILED; count[idx]++; } else { all_assigned = false; // We only need the counts in the view case or when all // x are assigned if (!Card::propagate) break; } }
if (Card::propagate) { // before propagation performs inferences on cardinality variables: if (noa > 0) for (int i = k.size(); i--; ) if (!k[i].assigned()) { GECODE_ME_CHECK(k[i].lq(home, x.size() - (noa - count[i]))); GECODE_ME_CHECK(k[i].gq(home, count[i])); }
if (!card_consistent<Card>(x, k)) return ES_FAILED;
GECODE_ES_CHECK(prop_card<Card>(home, x, k));
// Cardinalities may have been modified, so recompute // count and all_assigned for (int i = k.size(); i--; ) count[i] = 0; all_assigned = true; for (int i = x.size(); i--; ) { if (x[i].assigned()) { int idx; // reduction is essential for order on value nodes in dom // hence introduce test for failed lookup if (!lookupValue(k,x[i].val(),idx)) return ES_FAILED; count[idx]++; } else { // We won't need the remaining counts, they're only used when // all x are assigned all_assigned = false; break; } } }
if (all_assigned) { for (int i = k.size(); i--; ) GECODE_ME_CHECK(k[i].eq(home, count[i])); return home.ES_SUBSUMED(*this); }
if (Card::propagate) GECODE_ES_CHECK(pruneCards(home));
int n = x.size();
int* mu = r.alloc<int>(n); int* nu = r.alloc<int>(n);
for (int i = n; i--; ) nu[i] = mu[i] = i;
// Create sorting permutation mu according to the variables upper bounds MaxInc<IntView> max_inc(x); Support::quicksort<int, MaxInc<IntView> >(mu, n, max_inc);
// Create sorting permutation nu according to the variables lower bounds MinInc<IntView> min_inc(x); Support::quicksort<int, MinInc<IntView> >(nu, n, min_inc);
// Sort the cardinality bounds by index MinIdx<Card> min_idx; Support::quicksort<Card, MinIdx<Card> >(&k[0], k.size(), min_idx);
if (!lps) { assert(!ups); lps.init(home, k, false); ups.init(home, k, true); } else if (Card::propagate) { // if there has been a change to the cardinality variables // reconstruction of the partial sum structure is necessary if (lps.check_update_min(k)) lps.init(home, k, false); if (ups.check_update_max(k)) ups.init(home, k, true); }
// assert that the minimal value of the partial sum structure for // LBC is consistent with the smallest value a variable can take assert(lps.minValue() <= x[nu[0]].min()); // assert that the maximal value of the partial sum structure for // UBC is consistent with the largest value a variable can take
/* * Setup rank and bounds info * Since this implementation is based on the theory of Hall Intervals * additional datastructures are needed in order to represent these * intervals and the "partial-sum" data structure (cf."gcc/bnd-sup.hpp") * */
HallInfo* hall = r.alloc<HallInfo>(2 * n + 2); Rank* rank = r.alloc<Rank>(n);
int nb = 0; // setup bounds and rank int min = x[nu[0]].min(); int max = x[mu[0]].max() + 1; int last = lps.firstValue + 1; //equivalent to last = min -2 hall[0].bounds = last;
/* * First the algorithm merges the arrays minsorted and maxsorted * into bounds i.e. hall[].bounds contains the ordered union * of the lower and upper domain bounds including two sentinels * at the beginning and at the end of the set * ( the upper variable bounds in this union are increased by 1 ) */
{ int i = 0; int j = 0; while (true) { if (i < n && min < max) { if (min != last) { last = min; hall[++nb].bounds = last; } rank[nu[i]].min = nb; if (++i < n) min = x[nu[i]].min(); } else { if (max != last) { last = max; hall[++nb].bounds = last; } rank[mu[j]].max = nb; if (++j == n) break; max = x[mu[j]].max() + 1; } } }
int rightmost = nb + 1; // rightmost accesible value in bounds hall[rightmost].bounds = ups.lastValue + 1 ;
if (Card::propagate) { skip_lbc = true; for (int i = k.size(); i--; ) if (k[i].min() != 0) { skip_lbc = false; break; } }
if (!card_fixed && !skip_lbc) GECODE_ES_CHECK((lbc(home, nb, hall, rank, mu, nu)));
GECODE_ES_CHECK((ubc(home, nb, hall, rank, mu, nu)));
if (Card::propagate) GECODE_ES_CHECK(prop_card<Card>(home, x, k));
for (int i = k.size(); i--; ) count[i] = 0; for (int i = x.size(); i--; ) if (x[i].assigned()) { int idx; if (!lookupValue(k,x[i].val(),idx)) return ES_FAILED; count[idx]++; } else { // We won't need the remaining counts, they're only used when // all x are assigned return ES_NOFIX; }
for (int i = k.size(); i--; ) GECODE_ME_CHECK(k[i].eq(home, count[i]));
return home.ES_SUBSUMED(*this); }
template<class Card> ExecStatus Bnd<Card>::post(Home home, ViewArray<IntView>& x, ViewArray<Card>& k) { bool cardfix = true; for (int i=k.size(); i--; ) if (!k[i].assigned()) { cardfix = false; break; } bool nolbc = true; for (int i=k.size(); i--; ) if (k[i].min() != 0) { nolbc = false; break; }
GECODE_ES_CHECK(postSideConstraints<Card>(home, x, k));
if (isDistinct<Card>(x,k)) return Distinct::Bnd<IntView>::post(home,x);
(void) new (home) Bnd<Card>(home,x,k,cardfix,nolbc); return ES_OK; }
}}}
// STATISTICS: int-prop