Changeset 839:f3bc4e9b5f3a in lemon-main for lemon/network_simplex.h

Timestamp:

02/20/10 18:39:03 (14 years ago)

Author:

Peter Kovacs <kpeter@…>

Branch:

default

Phase:

public

Message:

New heuristics for MCF algorithms (#340)
and some implementation improvements.

• A useful heuristic is added to NetworkSimplex? to make the initial pivots faster.
• A powerful global update heuristic is added to CostScaling? and the implementation is reworked with various improvements.
• Better relabeling in CostScaling? to improve numerical stability and make the code faster.
• A small improvement is made in CapacityScaling? for better delta computation.
• Add notes to the classes about the usage of vector<char> instead of vector<bool> for efficiency reasons.

File:

• lemon/network_simplex.h (modified) (21 diffs)

lemon/network_simplex.h

@@ -165 +165 @@
 
     typedef std::vector<int> IntVector;
-    typedef std::vector<char> CharVector;
     typedef std::vector<Value> ValueVector;
     typedef std::vector<Cost> CostVector;
+    typedef std::vector<char> BoolVector;
+    // Note: vector<char> is used instead of vector<bool> for efficiency reasons
 
     // State constants for arcs
@@ -213 +214 @@
     IntVector _last_succ;
     IntVector _dirty_revs;
-    CharVector _forward;
-    CharVector _state;
+    BoolVector _forward;
+    BoolVector _state;
     int _root;
 
@@ -245 +246 @@
       const IntVector  &_target;
       const CostVector &_cost;
-      const CharVector &_state;
+      const BoolVector &_state;
       const CostVector &_pi;
       int &_in_arc;
@@ -266 +267 @@
       bool findEnteringArc() {
         Cost c;
-        for (int e = _next_arc; e < _search_arc_num; ++e) {
+        for (int e = _next_arc; e != _search_arc_num; ++e) {
           c = _state[e] * (_cost[e] + _pi[_source[e]] - _pi[_target[e]]);
           if (c < 0) {
@@ -274 +275 @@
           }
         }
-        for (int e = 0; e < _next_arc; ++e) {
+        for (int e = 0; e != _next_arc; ++e) {
           c = _state[e] * (_cost[e] + _pi[_source[e]] - _pi[_target[e]]);
           if (c < 0) {
@@ -297 +298 @@
       const IntVector  &_target;
       const CostVector &_cost;
-      const CharVector &_state;
+      const BoolVector &_state;
       const CostVector &_pi;
       int &_in_arc;
@@ -314 +315 @@
       bool findEnteringArc() {
         Cost c, min = 0;
-        for (int e = 0; e < _search_arc_num; ++e) {
+        for (int e = 0; e != _search_arc_num; ++e) {
           c = _state[e] * (_cost[e] + _pi[_source[e]] - _pi[_target[e]]);
           if (c < min) {
@@ -336 +337 @@
       const IntVector  &_target;
       const CostVector &_cost;
-      const CharVector &_state;
+      const BoolVector &_state;
       const CostVector &_pi;
       int &_in_arc;
@@ -355 +356 @@
       {
         // The main parameters of the pivot rule
-        const double BLOCK_SIZE_FACTOR = 0.5;
+        const double BLOCK_SIZE_FACTOR = 1.0;
         const int MIN_BLOCK_SIZE = 10;
 
@@ -368 +369 @@
         int cnt = _block_size;
         int e;
-        for (e = _next_arc; e < _search_arc_num; ++e) {
+        for (e = _next_arc; e != _search_arc_num; ++e) {
           c = _state[e] * (_cost[e] + _pi[_source[e]] - _pi[_target[e]]);
           if (c < min) {
@@ -379 +380 @@
           }
         }
-        for (e = 0; e < _next_arc; ++e) {
+        for (e = 0; e != _next_arc; ++e) {
           c = _state[e] * (_cost[e] + _pi[_source[e]] - _pi[_target[e]]);
           if (c < min) {
@@ -409 +410 @@
       const IntVector  &_target;
       const CostVector &_cost;
-      const CharVector &_state;
+      const BoolVector &_state;
       const CostVector &_pi;
       int &_in_arc;
@@ -470 +471 @@
         min = 0;
         _curr_length = 0;
-        for (e = _next_arc; e < _search_arc_num; ++e) {
+        for (e = _next_arc; e != _search_arc_num; ++e) {
           c = _state[e] * (_cost[e] + _pi[_source[e]] - _pi[_target[e]]);
           if (c < 0) {
@@ -481 +482 @@
           }
         }
-        for (e = 0; e < _next_arc; ++e) {
+        for (e = 0; e != _next_arc; ++e) {
           c = _state[e] * (_cost[e] + _pi[_source[e]] - _pi[_target[e]]);
           if (c < 0) {
@@ -512 +513 @@
       const IntVector  &_target;
       const CostVector &_cost;
-      const CharVector &_state;
+      const BoolVector &_state;
       const CostVector &_pi;
       int &_in_arc;
@@ -565 +566 @@
         // Check the current candidate list
         int e;
-        for (int i = 0; i < _curr_length; ++i) {
+        for (int i = 0; i != _curr_length; ++i) {
           e = _candidates[i];
           _cand_cost[e] = _state[e] *
@@ -578 +579 @@
         int limit = _head_length;
 
-        for (e = _next_arc; e < _search_arc_num; ++e) {
+        for (e = _next_arc; e != _search_arc_num; ++e) {
           _cand_cost[e] = _state[e] *
             (_cost[e] + _pi[_source[e]] - _pi[_target[e]]);
@@ -590 +591 @@
           }
         }
-        for (e = 0; e < _next_arc; ++e) {
+        for (e = 0; e != _next_arc; ++e) {
           _cand_cost[e] = _state[e] *
             (_cost[e] + _pi[_source[e]] - _pi[_target[e]]);
@@ -1329 +1330 @@
 
       // Update _rev_thread using the new _thread values
-      for (int i = 0; i < int(_dirty_revs.size()); ++i) {
+      for (int i = 0; i != int(_dirty_revs.size()); ++i) {
         u = _dirty_revs[i];
         _rev_thread[_thread[u]] = u;
@@ -1399 +1400 @@
         _pi[u] += sigma;
       }
+    }
+
+    // Heuristic initial pivots
+    bool initialPivots() {
+      Value curr, total = 0;
+      std::vector<Node> supply_nodes, demand_nodes;
+      for (NodeIt u(_graph); u != INVALID; ++u) {
+        curr = _supply[_node_id[u]];
+        if (curr > 0) {
+          total += curr;
+          supply_nodes.push_back(u);
+        }
+        else if (curr < 0) {
+          demand_nodes.push_back(u);
+        }
+      }
+      if (_sum_supply > 0) total -= _sum_supply;
+      if (total <= 0) return true;
+
+      IntVector arc_vector;
+      if (_sum_supply >= 0) {
+        if (supply_nodes.size() == 1 && demand_nodes.size() == 1) {
+          // Perform a reverse graph search from the sink to the source
+          typename GR::template NodeMap<bool> reached(_graph, false);
+          Node s = supply_nodes[0], t = demand_nodes[0];
+          std::vector<Node> stack;
+          reached[t] = true;
+          stack.push_back(t);
+          while (!stack.empty()) {
+            Node u, v = stack.back();
+            stack.pop_back();
+            if (v == s) break;
+            for (InArcIt a(_graph, v); a != INVALID; ++a) {
+              if (reached[u = _graph.source(a)]) continue;
+              int j = _arc_id[a];
+              if (_cap[j] >= total) {
+                arc_vector.push_back(j);
+                reached[u] = true;
+                stack.push_back(u);
+              }
+            }
+          }
+        } else {
+          // Find the min. cost incomming arc for each demand node
+          for (int i = 0; i != int(demand_nodes.size()); ++i) {
+            Node v = demand_nodes[i];
+            Cost c, min_cost = std::numeric_limits<Cost>::max();
+            Arc min_arc = INVALID;
+            for (InArcIt a(_graph, v); a != INVALID; ++a) {
+              c = _cost[_arc_id[a]];
+              if (c < min_cost) {
+                min_cost = c;
+                min_arc = a;
+              }
+            }
+            if (min_arc != INVALID) {
+              arc_vector.push_back(_arc_id[min_arc]);
+            }
+          }
+        }
+      } else {
+        // Find the min. cost outgoing arc for each supply node
+        for (int i = 0; i != int(supply_nodes.size()); ++i) {
+          Node u = supply_nodes[i];
+          Cost c, min_cost = std::numeric_limits<Cost>::max();
+          Arc min_arc = INVALID;
+          for (OutArcIt a(_graph, u); a != INVALID; ++a) {
+            c = _cost[_arc_id[a]];
+            if (c < min_cost) {
+              min_cost = c;
+              min_arc = a;
+            }
+          }
+          if (min_arc != INVALID) {
+            arc_vector.push_back(_arc_id[min_arc]);
+          }
+        }
+      }
+
+      // Perform heuristic initial pivots
+      for (int i = 0; i != int(arc_vector.size()); ++i) {
+        in_arc = arc_vector[i];
+        if (_state[in_arc] * (_cost[in_arc] + _pi[_source[in_arc]] -
+            _pi[_target[in_arc]]) >= 0) continue;
+        findJoinNode();
+        bool change = findLeavingArc();
+        if (delta >= MAX) return false;
+        changeFlow(change);
+        if (change) {
+          updateTreeStructure();
+          updatePotential();
+        }
+      }
+      return true;
     }
 
@@ -1423 +1518 @@
       PivotRuleImpl pivot(*this);
 
+      // Perform heuristic initial pivots
+      if (!initialPivots()) return UNBOUNDED;
+
       // Execute the Network Simplex algorithm
       while (pivot.findEnteringArc()) {