| ... | ... |
@@ -119,20 +119,23 @@ |
| 119 | 119 |
|
| 120 | 120 |
/// \brief Constants for selecting the pivot rule. |
| 121 | 121 |
/// |
| 122 | 122 |
/// Enum type containing constants for selecting the pivot rule for |
| 123 | 123 |
/// the \ref run() function. |
| 124 | 124 |
/// |
| 125 |
/// \ref NetworkSimplex provides five different pivot rule |
|
| 126 |
/// implementations that significantly affect the running time |
|
| 125 |
/// \ref NetworkSimplex provides five different implementations for |
|
| 126 |
/// the pivot strategy that significantly affects the running time |
|
| 127 | 127 |
/// of the algorithm. |
| 128 |
/// By default, \ref BLOCK_SEARCH "Block Search" is used, which |
|
| 129 |
/// turend out to be the most efficient and the most robust on various |
|
| 130 |
/// test inputs. |
|
| 131 |
/// However, another pivot rule can be selected using the \ref run() |
|
| 132 |
/// |
|
| 128 |
/// According to experimental tests conducted on various problem |
|
| 129 |
/// instances, \ref BLOCK_SEARCH "Block Search" and |
|
| 130 |
/// \ref ALTERING_LIST "Altering Candidate List" rules turned out |
|
| 131 |
/// to be the most efficient. |
|
| 132 |
/// Since \ref BLOCK_SEARCH "Block Search" is a simpler strategy that |
|
| 133 |
/// seemed to be slightly more robust, it is used by default. |
|
| 134 |
/// However, another pivot rule can easily be selected using the |
|
| 135 |
/// \ref run() function with the proper parameter. |
|
| 133 | 136 |
enum PivotRule {
|
| 134 | 137 |
|
| 135 | 138 |
/// The \e First \e Eligible pivot rule. |
| 136 | 139 |
/// The next eligible arc is selected in a wraparound fashion |
| 137 | 140 |
/// in every iteration. |
| 138 | 141 |
FIRST_ELIGIBLE, |
| ... | ... |
@@ -152,13 +155,13 @@ |
| 152 | 155 |
/// in a wraparound fashion and in the following minor iterations |
| 153 | 156 |
/// the best eligible arc is selected from this list. |
| 154 | 157 |
CANDIDATE_LIST, |
| 155 | 158 |
|
| 156 | 159 |
/// The \e Altering \e Candidate \e List pivot rule. |
| 157 | 160 |
/// It is a modified version of the Candidate List method. |
| 158 |
/// It keeps only |
|
| 161 |
/// It keeps only a few of the best eligible arcs from the former |
|
| 159 | 162 |
/// candidate list and extends this list in every iteration. |
| 160 | 163 |
ALTERING_LIST |
| 161 | 164 |
}; |
| 162 | 165 |
|
| 163 | 166 |
private: |
| 164 | 167 |
|
| ... | ... |
@@ -535,13 +538,13 @@ |
| 535 | 538 |
{
|
| 536 | 539 |
private: |
| 537 | 540 |
const CostVector &_map; |
| 538 | 541 |
public: |
| 539 | 542 |
SortFunc(const CostVector &map) : _map(map) {}
|
| 540 | 543 |
bool operator()(int left, int right) {
|
| 541 |
return _map[left] |
|
| 544 |
return _map[left] < _map[right]; |
|
| 542 | 545 |
} |
| 543 | 546 |
}; |
| 544 | 547 |
|
| 545 | 548 |
SortFunc _sort_func; |
| 546 | 549 |
|
| 547 | 550 |
public: |
| ... | ... |
@@ -553,13 +556,13 @@ |
| 553 | 556 |
_in_arc(ns.in_arc), _search_arc_num(ns._search_arc_num), |
| 554 | 557 |
_next_arc(0), _cand_cost(ns._search_arc_num), _sort_func(_cand_cost) |
| 555 | 558 |
{
|
| 556 | 559 |
// The main parameters of the pivot rule |
| 557 | 560 |
const double BLOCK_SIZE_FACTOR = 1.0; |
| 558 | 561 |
const int MIN_BLOCK_SIZE = 10; |
| 559 |
const double HEAD_LENGTH_FACTOR = 0. |
|
| 562 |
const double HEAD_LENGTH_FACTOR = 0.01; |
|
| 560 | 563 |
const int MIN_HEAD_LENGTH = 3; |
| 561 | 564 |
|
| 562 | 565 |
_block_size = std::max( int(BLOCK_SIZE_FACTOR * |
| 563 | 566 |
std::sqrt(double(_search_arc_num))), |
| 564 | 567 |
MIN_BLOCK_SIZE ); |
| 565 | 568 |
_head_length = std::max( int(HEAD_LENGTH_FACTOR * _block_size), |
| ... | ... |
@@ -597,37 +600,37 @@ |
| 597 | 600 |
if (_curr_length > limit) goto search_end; |
| 598 | 601 |
limit = 0; |
| 599 | 602 |
cnt = _block_size; |
| 600 | 603 |
} |
| 601 | 604 |
} |
| 602 | 605 |
for (e = 0; e != _next_arc; ++e) {
|
| 603 |
_cand_cost[e] = _state[e] * |
|
| 604 |
(_cost[e] + _pi[_source[e]] - _pi[_target[e]]); |
|
| 605 |
|
|
| 606 |
c = _state[e] * (_cost[e] + _pi[_source[e]] - _pi[_target[e]]); |
|
| 607 |
if (c < 0) {
|
|
| 608 |
_cand_cost[e] = c; |
|
| 606 | 609 |
_candidates[_curr_length++] = e; |
| 607 | 610 |
} |
| 608 | 611 |
if (--cnt == 0) {
|
| 609 | 612 |
if (_curr_length > limit) goto search_end; |
| 610 | 613 |
limit = 0; |
| 611 | 614 |
cnt = _block_size; |
| 612 | 615 |
} |
| 613 | 616 |
} |
| 614 | 617 |
if (_curr_length == 0) return false; |
| 615 | 618 |
|
| 616 | 619 |
search_end: |
| 617 | 620 |
|
| 618 |
// Make heap of the candidate list (approximating a partial sort) |
|
| 619 |
make_heap( _candidates.begin(), _candidates.begin() + _curr_length, |
|
| 620 |
|
|
| 621 |
// Perform partial sort operation on the candidate list |
|
| 622 |
int new_length = std::min(_head_length + 1, _curr_length); |
|
| 623 |
std::partial_sort(_candidates.begin(), _candidates.begin() + new_length, |
|
| 624 |
_candidates.begin() + _curr_length, _sort_func); |
|
| 621 | 625 |
|
| 622 |
// |
|
| 626 |
// Select the entering arc and remove it from the list |
|
| 623 | 627 |
_in_arc = _candidates[0]; |
| 624 | 628 |
_next_arc = e; |
| 625 |
pop_heap( _candidates.begin(), _candidates.begin() + _curr_length, |
|
| 626 |
_sort_func ); |
|
| 627 |
|
|
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_candidates[0] = _candidates[new_length - 1]; |
|
| 630 |
_curr_length = new_length - 1; |
|
| 628 | 631 |
return true; |
| 629 | 632 |
} |
| 630 | 633 |
|
| 631 | 634 |
}; //class AlteringListPivotRule |
| 632 | 635 |
|
| 633 | 636 |
public: |
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