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alpar (Alpar Juttner)
alpar@cs.elte.hu
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Ignore white space 16 line context
... ...
@@ -117,24 +117,27 @@
117 117
      LEQ
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    };
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    /// \brief Constants for selecting the pivot rule.
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    ///
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    /// Enum type containing constants for selecting the pivot rule for
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    /// the \ref run() function.
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    ///
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    /// \ref NetworkSimplex provides five different pivot rule
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    /// implementations that significantly affect the running time
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    /// \ref NetworkSimplex provides five different implementations for
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    /// the pivot strategy that significantly affects the running time
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    /// of the algorithm.
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    /// By default, \ref BLOCK_SEARCH "Block Search" is used, which
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    /// turend out to be the most efficient and the most robust on various
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    /// test inputs.
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    /// However, another pivot rule can be selected using the \ref run()
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    /// function with the proper parameter.
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    /// According to experimental tests conducted on various problem
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    /// instances, \ref BLOCK_SEARCH "Block Search" and
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    /// \ref ALTERING_LIST "Altering Candidate List" rules turned out
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    /// to be the most efficient.
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    /// Since \ref BLOCK_SEARCH "Block Search" is a simpler strategy that
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    /// seemed to be slightly more robust, it is used by default.
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    /// However, another pivot rule can easily be selected using the
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    /// \ref run() function with the proper parameter.
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    enum PivotRule {
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      /// The \e First \e Eligible pivot rule.
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      /// The next eligible arc is selected in a wraparound fashion
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      /// in every iteration.
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      FIRST_ELIGIBLE,
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      /// The \e Best \e Eligible pivot rule.
... ...
@@ -150,17 +153,17 @@
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      /// The \e Candidate \e List pivot rule.
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      /// In a major iteration a candidate list is built from eligible arcs
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      /// in a wraparound fashion and in the following minor iterations
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      /// the best eligible arc is selected from this list.
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      CANDIDATE_LIST,
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      /// The \e Altering \e Candidate \e List pivot rule.
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      /// It is a modified version of the Candidate List method.
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      /// It keeps only the several best eligible arcs from the former
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      /// It keeps only a few of the best eligible arcs from the former
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      /// candidate list and extends this list in every iteration.
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      ALTERING_LIST
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    };
162 165

	
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  private:
164 167

	
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    TEMPLATE_DIGRAPH_TYPEDEFS(GR);
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... ...
@@ -533,17 +536,17 @@
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      // Functor class to compare arcs during sort of the candidate list
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      class SortFunc
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      {
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      private:
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        const CostVector &_map;
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      public:
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        SortFunc(const CostVector &map) : _map(map) {}
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        bool operator()(int left, int right) {
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          return _map[left] > _map[right];
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          return _map[left] < _map[right];
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        }
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      };
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      SortFunc _sort_func;
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    public:
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      // Constructor
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@@ -551,17 +554,17 @@
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        _source(ns._source), _target(ns._target),
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        _cost(ns._cost), _state(ns._state), _pi(ns._pi),
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        _in_arc(ns.in_arc), _search_arc_num(ns._search_arc_num),
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        _next_arc(0), _cand_cost(ns._search_arc_num), _sort_func(_cand_cost)
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      {
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        // The main parameters of the pivot rule
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        const double BLOCK_SIZE_FACTOR = 1.0;
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        const int MIN_BLOCK_SIZE = 10;
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        const double HEAD_LENGTH_FACTOR = 0.1;
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        const double HEAD_LENGTH_FACTOR = 0.01;
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        const int MIN_HEAD_LENGTH = 3;
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        _block_size = std::max( int(BLOCK_SIZE_FACTOR *
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                                    std::sqrt(double(_search_arc_num))),
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                                MIN_BLOCK_SIZE );
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        _head_length = std::max( int(HEAD_LENGTH_FACTOR * _block_size),
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                                 MIN_HEAD_LENGTH );
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        _candidates.resize(_head_length + _block_size);
... ...
@@ -595,41 +598,41 @@
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          }
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          if (--cnt == 0) {
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            if (_curr_length > limit) goto search_end;
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            limit = 0;
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            cnt = _block_size;
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          }
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        }
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        for (e = 0; e != _next_arc; ++e) {
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          _cand_cost[e] = _state[e] *
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            (_cost[e] + _pi[_source[e]] - _pi[_target[e]]);
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          if (_cand_cost[e] < 0) {
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          c = _state[e] * (_cost[e] + _pi[_source[e]] - _pi[_target[e]]);
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          if (c < 0) {
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            _cand_cost[e] = c;
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            _candidates[_curr_length++] = e;
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          }
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          if (--cnt == 0) {
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            if (_curr_length > limit) goto search_end;
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            limit = 0;
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            cnt = _block_size;
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          }
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        }
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        if (_curr_length == 0) return false;
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      search_end:
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        // Make heap of the candidate list (approximating a partial sort)
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        make_heap( _candidates.begin(), _candidates.begin() + _curr_length,
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                   _sort_func );
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        // Perform partial sort operation on the candidate list
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        int new_length = std::min(_head_length + 1, _curr_length);
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        std::partial_sort(_candidates.begin(), _candidates.begin() + new_length,
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                          _candidates.begin() + _curr_length, _sort_func);
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        // Pop the first element of the heap
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        // Select the entering arc and remove it from the list
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        _in_arc = _candidates[0];
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        _next_arc = e;
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        pop_heap( _candidates.begin(), _candidates.begin() + _curr_length,
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                  _sort_func );
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        _curr_length = std::min(_head_length, _curr_length - 1);
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        _candidates[0] = _candidates[new_length - 1];
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        _curr_length = new_length - 1;
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        return true;
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      }
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    }; //class AlteringListPivotRule
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  public:
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    /// \brief Constructor.
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