tpl_netcost.H

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/*
                          Aleph_w
 
  Data structures & Algorithms
  version 2.0.0b
  https://github.com/lrleon/Aleph-w
 
  This file is part of Aleph-w library
 
  Copyright (c) 2002-2026 Leandro Rabindranath Leon
 
  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:
 
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  THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
  IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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*/
 
 
# ifndef TPL_NETCOST_H
# define TPL_NETCOST_H
 
# include <ah-graph-concepts.H>
 
# include <limits>
# include <chrono>
# include <tpl_net.H>
# include <tpl_dynMapTree.H>
# include <tpl_find_path.H>
# include <tpl_cut_nodes.H>
# include <Bellman_Ford.H>
# include <generate_graph.H>
# include <ah-errors.H>
 
namespace Aleph
{
  template <typename Node_Info = Empty_Class>
  using Net_Cost_Node = Net_Node<Node_Info>;
 
 
  template <typename Arc_Info = Empty_Class, typename F_Type = double>
  struct Net_Cost_Arc : public Net_Arc<Arc_Info, F_Type>
  {
    using Base = Net_Arc<Arc_Info, F_Type>;
    using Base::Base;
 
    using Flow_Type = F_Type;
 
    Flow_Type cost = 0;
 
    Net_Cost_Arc() = default;
 
    Net_Cost_Arc(const Net_Cost_Arc & a)
      : Base(a), cost(a.cost)
    { /* empty */
    }
 
    Net_Cost_Arc &operator =(const Net_Cost_Arc & a)
    {
      if (&a == this)
        return *this;
      Base::operator=(a);
      cost = a.cost;
      return *this;
    }
 
    Flow_Type flow_cost() const noexcept { return this->flow * cost; }
  };
 
 
  template <class NodeT = Net_Cost_Node<Empty_Class>,
            class ArcT = Net_Cost_Arc<Empty_Class, double>>
  struct Net_Cost_Graph : public Net_Graph<NodeT, ArcT>
  {
    using Base = Net_Graph<NodeT, ArcT>;
 
    using Net = Net_Graph<NodeT, ArcT>;
 
    using Net_MFMC = Net_Cost_Graph<NodeT, ArcT>;
 
    using Arc = ArcT;
 
    using Node = NodeT;
 
    using Flow_Type = typename Arc::Flow_Type;
 
    using Node_Type = typename Node::Node_Type;
 
    using Arc_Type = typename Arc::Arc_Type;
 
    Net_Cost_Graph() = default;
 
    Net_Cost_Graph(const Net_Cost_Graph & net) : Base(net)
    {
      zip(this->arcs(), net.arcs()).for_each([](const auto & p)
                                               {
                                                 auto atgt = p.first;
                                                 auto asrc = p.second;
                                                 atgt->cost = asrc->cost;
                                               });
    }
 
    Net_Cost_Graph(Net_Cost_Graph &&) = default;
 
    Net_Cost_Graph &operator =(const Net_Cost_Graph & net)
    {
      if (this == &net)
        return *this;
      Net_Cost_Graph tmp(net);  // copy construct (copies capacity, flow, and cost)
      this->swap(tmp);          // swap with copy
      return *this;
    }
 
    Net_Cost_Graph &operator =(Net_Cost_Graph &&) = default;
 
    Flow_Type &get_cost(Arc *a) noexcept { return a->cost; }
 
    Flow_Type get_cost(Arc *a) const noexcept { return a->cost; }
 
    static Flow_Type arc_flow_cost(Arc *a) noexcept { return a->flow_cost(); }
 
    virtual Arc * insert_arc(Node *src_node, Node *tgt_node,
                             const Flow_Type & cap, const Flow_Type & __cost)
    {
      Arc *a = Net::insert_arc(src_node, tgt_node, cap, 0, Arc_Type());
      a->cost = __cost;
      return a;
    }
 
    template <typename... Args>
    Arc * emplace_arc(Node *src_node, Node *tgt_node,
                      const Flow_Type & cap, const Flow_Type & __cost,
                      Args &&... args)
    {
      auto a = Net::insert_arc(src_node, tgt_node, cap, 0,
                               Arc_Type(std::forward<Args>(args)...));
      a->cost = __cost;
      return a;
    }
 
    virtual Arc * insert_arc(Node *src_node, Node *tgt_node)
    {
      Arc *a = Net::insert_arc(src_node, tgt_node, Arc_Type());
      a->cost = 0;
      return a;
    }
 
    Flow_Type flow_cost() const
    {
      Flow_Type total = 0;
      for (Arc_Iterator<Net_MFMC> it(*this); it.has_curr(); it.next_ne())
        {
          Arc *a = it.get_curr();
          total += a->flow_cost();
        }
      return total;
    }
 
    auto out_pars(Node *p)
    {
      Flow_Type cap_sum = 0, flow_sum = 0, cost_sum = 0;
      for (_Out_Iterator<Net> it(p); it.has_curr(); it.next_ne())
        {
          Arc *a = it.get_curr();
          cap_sum += a->cap;
          flow_sum += a->flow;
          cost_sum += a->cost;
        }
      return std::make_tuple(cap_sum, flow_sum, cost_sum);
    }
 
    auto in_pars(Node *p)
    {
      Flow_Type cap_sum = 0, flow_sum = 0, cost_sum = 0;
      for (_In_Iterator<Net> it(p); it.has_curr(); it.next_ne())
        {
          Arc *a = it.get_curr();
          cap_sum += a->cap;
          flow_sum += a->flow;
          cost_sum += a->cost;
        }
      return std::make_tuple(cap_sum, flow_sum, cost_sum);
    }
  };
 
 
  template <class Net>
  struct Res_Filt
  {
    Res_Filt(typename Net::Node *) noexcept {}
 
    Res_Filt() noexcept = default;
 
    bool operator ()(typename Net::Arc *a) const noexcept
    {
      return a->cap > a->flow;
    }
  };
 
 
  template <class Net>
  struct Rcost
  {
    Rcost() noexcept = default;
 
    using Distance_Type = typename Net::Flow_Type;
 
    typename Net::Flow_Type operator ()(typename Net::Arc *a) const noexcept
    {
      return a->cost;
    }
 
    static void set_zero(typename Net::Arc *a) noexcept
    {
      a->cap = std::numeric_limits<Distance_Type>::max();
      a->flow = 0;
      a->cost = 0;
    }
  };
 
 
  template <typename Ftype>
  struct Res_Arc : public Net_Cost_Arc<Empty_Class, Ftype>
  {
    using Base = Net_Cost_Arc<Empty_Class, Ftype>;
    using Base::Base;
 
    bool is_residual = false;
 
    Res_Arc *img = nullptr;
  };
 
 
  template <typename Ftype>
  using Residual_Net = Net_Cost_Graph<Net_Node<Empty_Class>, Res_Arc<Ftype>>;
 
 
  template <class Res_Net>
  typename Res_Net::Arc *
  create_residual_arc(Res_Net & residual_net,
                      typename Res_Net::Node *src,
                      typename Res_Net::Node *tgt,
                      const typename Res_Net::Flow_Type cap,
                      const typename Res_Net::Flow_Type flow,
                      const typename Res_Net::Flow_Type cost)
  {
    assert(flow <= cap and cost >= 0);
 
    auto arc = residual_net.insert_arc(src, tgt, cap, cost);
    auto rarc = residual_net.insert_arc(tgt, src, cap, -cost);
 
    arc->is_residual = false;
    arc->flow = flow;
    arc->img = rarc;
 
    rarc->is_residual = true;
    rarc->img = arc;
    rarc->flow = arc->cap - arc->flow;
 
    assert(arc->cap == cap and arc->flow == flow and arc->cost == cost);
    assert(rarc->cap == cap and rarc->flow == cap - flow and rarc->cost == -cost);
 
    return arc;
  }
 
 
  template <class Net>
  typename Residual_Net<typename Net::Flow_Type>::Node *
  build_residual_net(const Net & net,
                     Residual_Net<typename Net::Flow_Type> & rnet,
                     DynMapTree<void *, void *> & arcs)
  {
    ah_domain_error_if(not (net.is_single_source() and net.is_single_sink()))
      << "Network is not single source and single sink";
 
    using Rnet = Residual_Net<typename Net::Flow_Type>;
 
    // Copy nodes from net to residual network
    for (typename Net::Node_Iterator it(net); it.has_curr(); it.next_ne())
      {
        auto p = it.get_curr();
        auto q = rnet.insert_node();
        map_nodes<Net, Rnet>(p, q);
      }
 
    // Create residual arcs and build mapping
    for (typename Net::Arc_Iterator it(net); it.has_curr(); it.next_ne())
      {
        auto ga = it.get_curr();
        auto gsrc = static_cast<typename Net::Node *>(ga->src_node);
        auto gtgt = static_cast<typename Net::Node *>(ga->tgt_node);
 
        auto rsrc = mapped_node<Net, Rnet>(gsrc);
        auto rtgt = mapped_node<Net, Rnet>(gtgt);
        auto ra = create_residual_arc(rnet, rsrc, rtgt,
                                      ga->cap, ga->flow, ga->cost);
        arcs.insert(ga, ra);
      }
 
    assert(check_residual_net(rnet));
 
    return static_cast<typename Rnet::Node *>(NODE_COOKIE(net.get_source()));
  }
 
 
  template <class Res_Net>
  bool check_residual_net(const Res_Net & net)
  {
    return net.all_arcs([](typename Res_Net::Arc *a)
                          {
                            return a->img != nullptr and a->img->img == a;
                          });
  }
 
 
  template <class Res_Net>
  void cancel_cycle(const Res_Net &, const Path<Res_Net> & path)
  {
    ah_domain_error_if(path.is_empty() or not path.is_cycle())
      << "Path is empty or not a cycle";
 
    using Ftype = typename Res_Net::Flow_Type;
 
    // Determine minimum slack (bottleneck capacity) of the cycle
    Ftype slack = std::numeric_limits<Ftype>::max();
    path.for_each_arc([&slack](typename Res_Net::Arc *a)
                        {
                          assert(a->cap - a->flow > 0);
                          slack = std::min(slack, a->cap - a->flow);
                        });
 
    // Cancel the cycle by augmenting flow
    path.for_each_arc([slack](typename Res_Net::Arc *a)
                        {
                          auto img = a->img;
                          assert(img->img == a);
                          assert(a->cap == img->cap);
                          a->flow += slack;
                          img->flow -= slack;
                        });
  }
 
 
  template <class Net>
  void residual_to_net(const DynMapTree<void *, void *> & arcs)
  {
    using Rnet = Residual_Net<typename Net::Flow_Type>;
    arcs.for_each([](std::pair<void *, void *> p)
                    {
                      auto net_arc = static_cast<typename Net::Arc *>(p.first);
                      auto res_arc = static_cast<typename Rnet::Arc *>(p.second);
                      net_arc->flow = res_arc->flow;
                    });
  }
 
 
  template <FlowNetwork Net,
            template <class> class Max_Flow_Algo = Ford_Fulkerson_Maximum_Flow>
  std::tuple<size_t, double>
  max_flow_min_cost_by_cycle_canceling(Net & net,
                                       double it_factor = 0.4,
                                       size_t step = 10)
  {
    Max_Flow_Algo<Net>()(net); // First compute maximum flow
 
    using Rnet = Residual_Net<typename Net::Flow_Type>;
    using BF = Bellman_Ford<Rnet, Rcost<Rnet>, Arc_Iterator,
                            Out_Iterator, Res_Filt<Rnet>>;
 
    // Build residual network
    Rnet rnet;
    DynMapTree<void *, void *> arcs_map;
    typename Rnet::Node *source = build_residual_net(net, rnet, arcs_map);
 
    size_t count = 0;
    bool found_cycle = true;
 
    // Main loop: find and cancel negative cycles
    while (found_cycle)
      {
        // Search for negative cycle from source
        auto [cycle, iterations] =
            BF(rnet).search_negative_cycle(source, it_factor, step);
 
        if (cycle.is_empty())
          {
            // No cycle found from source, try global search
            auto [global_cycle, global_iter] =
                BF(rnet).search_negative_cycle(it_factor, step);
 
            if (global_cycle.is_empty())
              found_cycle = false;
            else
              {
                cancel_cycle(rnet, global_cycle);
                ++count;
              }
          }
        else
          { // Update iteration factor based on when cycle was found
            it_factor = static_cast<double>(iterations) / net.vsize();
            cancel_cycle(rnet, cycle);
            ++count;
          }
      }
 
    // Transfer results back to original network
    residual_to_net<Net>(arcs_map);
 
    return std::make_tuple(count, it_factor);
  }
 
 
  template <FlowNetwork Net,
            template <class> class Max_Flow_Algo = Ford_Fulkerson_Maximum_Flow>
  struct Max_Flow_Min_Cost_By_Cycle_Canceling
  {
    std::tuple<size_t, double> operator ()(Net & net,
                                           const double it_factor = 0.4,
                                           const size_t step = 10)
    {
      return max_flow_min_cost_by_cycle_canceling<Net, Max_Flow_Algo>
          (net, it_factor, step);
    }
  };
 
 
  template <class Net>
  void print_net_cost(const Net & net, std::ostream & out)
  {
    long i = 0;
    net.nodes().for_each([&i](typename Net::Node *p)
                           {
                             NODE_COUNTER(p) = i++;
                           });
 
    struct Show_Node
    {
      void operator ()(const Net &, typename Net::Node *p, std::ostream & o)
      {
        o << "label = \"(" << p->get_info() << "," << NODE_COUNTER(p) << ")\"";
      }
    };
 
    struct Show_Arc
    {
      void operator ()(const Net &, typename Net::Arc *a, std::ostream & o)
      {
        o << "label = \"" << a->flow << "/" << a->cap << "/" << a->cost << "\"";
      }
    };
 
    To_Graphviz<Net, Show_Node, Show_Arc>().digraph(net, out);
  }
 
 
  template <class Net>
  void print_residual_net(const Residual_Net<typename Net::Flow_Type> & net,
                          std::ostream & out)
  {
    using Rnet = Residual_Net<typename Net::Flow_Type>;
 
    long i = 0;
    net.nodes().for_each([&i](typename Rnet::Node *p)
                           {
                             NODE_COUNTER(p) = i++;
                           });
 
    struct Show_Node
    {
      void operator ()(const Rnet &, typename Rnet::Node *p, std::ostream & o)
      {
        o << "label = \"" << NODE_COUNTER(p) << "\"";
      }
    };
 
    struct Show_Arc
    {
      void operator ()(const Rnet &, typename Rnet::Arc *a, std::ostream & o)
      {
        o << "label = \"" << a->flow << "/" << a->cap << "/" << a->cost << "\"";
        if (a->is_residual)
          o << " color = red";
      }
    };
 
    To_Graphviz<Rnet, Show_Node, Show_Arc, Dft_Show_Node<Rnet>,
                Res_Filt<Rnet>>().digraph(net, out);
  }
 
 
  // =========================================================================
  // Network Simplex Algorithm Implementation
  // =========================================================================
 
  template <class Net>
  using Feasible_Tree = std::tuple<DynList<typename Net::Arc *>,
                                   DynList<typename Net::Arc *>,
                                   DynList<typename Net::Arc *>>;
 
 
  template <class Net>
  inline Feasible_Tree<Net> build_feasible_spanning_tree(const Net & net)
  {
    using Arc = typename Net::Arc;
    DynList<Arc *> empty, full, partial;
 
    for (typename Net::Arc_Iterator it(net); it.has_curr(); it.next_ne())
      {
        if (auto a = it.get_curr(); a->flow == 0)
          empty.append(a);
        else if (a->flow == a->cap)
          full.append(a);
        else
          partial.append(a);
      }
 
    return std::make_tuple(std::move(empty), std::move(full), std::move(partial));
  }
 
 
  template <class Net>
  inline DynList<typename Net::Arc *> get_partial_arcs(const Net & net)
  {
    DynList<typename Net::Arc *> ret;
    for (typename Net::Arc_Iterator it(net); it.has_curr(); it.next_ne())
      if (auto a = it.get_curr(); a->flow > 0 and a->flow < a->cap)
        ret.append(a);
    return ret;
  }
 
 
  template <typename Ftype>
  struct Simplex_Node_Info
  {
    Ftype potential = 0;
 
    void *parent = nullptr;
 
    void *parent_arc = nullptr;
 
    long depth = 0;
 
    bool arc_from_parent = true;
 
    long mark = 0;
  };
 
 
  enum class Simplex_Arc_State : unsigned char
  {
    Lower,  
    Upper,  
    Tree    
  };
 
 
  template <typename Ftype>
  struct Simplex_Arc_Info
  {
    Simplex_Arc_State state = Simplex_Arc_State::Lower;
    bool skip = false;
    Ftype lower_bound = Ftype{0};
  };
 
 
  struct NetworkSimplexStats
  {
    size_t total_pivots = 0;         
    size_t phase1_pivots = 0;        
    size_t phase2_pivots = 0;        
    size_t degenerate_pivots = 0;    
    size_t tree_arcs = 0;            
    double phase1_time_ms = 0.0;     
    double phase2_time_ms = 0.0;     
    double total_time_ms = 0.0;      
    size_t initial_partial_arcs = 0; 
    size_t forced_into_tree = 0;     
 
    void reset() noexcept
    {
      total_pivots = 0;
      phase1_pivots = 0;
      phase2_pivots = 0;
      degenerate_pivots = 0;
      tree_arcs = 0;
      phase1_time_ms = 0.0;
      phase2_time_ms = 0.0;
      total_time_ms = 0.0;
      initial_partial_arcs = 0;
      forced_into_tree = 0;
    }
  };
 
 
  template <FlowNetwork Net>
  class Network_Simplex
  {
  public:
    using Node = typename Net::Node;
    using Arc = typename Net::Arc;
    using Flow_Type = typename Net::Flow_Type;
    using Node_Info = Simplex_Node_Info<Flow_Type>;
    using Arc_Info = Simplex_Arc_Info<Flow_Type>;
 
  private:
    Net &net;
    DynArray<Node_Info> node_info;
    DynArray<Arc_Info> arc_info;
    DynMapTree<Node *, size_t> node_to_idx;
    DynMapTree<Arc *, size_t> arc_to_idx;
    Node *root = nullptr;
    size_t num_pivots = 0;
    long lca_mark = 0;  // Counter for LCA marking
    mutable NetworkSimplexStats stats;
    bool support_lower_bounds = false;
 
    static constexpr Flow_Type Inf = std::numeric_limits<Flow_Type>::max();
 
    static Flow_Type eps()
    {
      if constexpr (std::is_floating_point_v<Flow_Type>)
        return std::numeric_limits<Flow_Type>::epsilon() * 1000;
      else
        return 0;
    }
 
    Node_Info &ninfo(Node *p) { return node_info(node_to_idx.find(p)); }
 
    const Node_Info &ninfo(Node *p) const { return node_info(node_to_idx.find(p)); }
 
    Arc_Info &ainfo(Arc *a) { return arc_info(arc_to_idx.find(a)); }
 
    const Arc_Info &ainfo(Arc *a) const { return arc_info(arc_to_idx.find(a)); }
 
    Node *parent(Node *p) const { return static_cast<Node *>(ninfo(p).parent); }
 
    Arc *parent_arc(Node *p) const { return static_cast<Arc *>(ninfo(p).parent_arc); }
 
    long depth(Node *p) const { return ninfo(p).depth; }
 
    Flow_Type potential(Node *p) const { return ninfo(p).potential; }
 
    bool is_zero(Flow_Type x) const
    {
      if constexpr (std::is_floating_point_v<Flow_Type>)
        return std::abs(x) <= eps();
      else
        return x == 0;
    }
 
    Flow_Type reduced_cost(Arc *a) const
    {
      auto src = static_cast<Node *>(a->src_node);
      auto tgt = static_cast<Node *>(a->tgt_node);
      return a->cost - ninfo(src).potential + ninfo(tgt).potential;
    }
 
    void init_structures()
    {
      node_info.cut(0);
      arc_info.cut(0);
      node_to_idx.empty();
      arc_to_idx.empty();
 
      // Map nodes to indices
      size_t idx = 0;
      for (typename Net::Node_Iterator it(net); it.has_curr(); it.next_ne())
        {
          auto p = it.get_curr();
          node_to_idx.insert(p, idx);
          node_info.touch(idx) = Node_Info{};
          ++idx;
        }
 
      // Map arcs to indices - DO NOT classify yet, let build_spanning_tree handle it
      idx = 0;
      for (typename Net::Arc_Iterator it(net); it.has_curr(); it.next_ne())
        {
          auto a = it.get_curr();
          arc_to_idx.insert(a, idx);
          arc_info.touch(idx) = Arc_Info{};
          // Initially mark all arcs as Lower; build_spanning_tree will fix this
          arc_info(idx).state = Simplex_Arc_State::Lower;
          ++idx;
        }
    }
 
    bool is_partial_flow(Arc *a) const
    {
      return a->flow > eps() and a->flow < a->cap - eps();
    }
 
    void build_spanning_tree()
    {
      root = net.get_source();
 
      // Reset all nodes
      for (typename Net::Node_Iterator it(net); it.has_curr(); it.next_ne())
        {
          auto p = it.get_curr();
          auto &ni = ninfo(p);
          ni.parent = nullptr;
          ni.parent_arc = nullptr;
          ni.depth = -1;
          ni.potential = 0;
          ni.mark = 0;
        }
 
      // Reset all arcs to Lower
      for (typename Net::Arc_Iterator it(net); it.has_curr(); it.next_ne())
        ainfo(it.get_curr()).state = Simplex_Arc_State::Lower;
 
      const size_t total_nodes = net.vsize();
      DynListQueue<Node *> queue;
      queue.put(root);
      ninfo(root).depth = 0;
      ninfo(root).potential = 0;
 
      size_t nodes_in_tree = 1;
 
      // Helper to add a node to tree via an arc
      auto add_to_tree = [&](Node *p, Arc *a, Node *other) -> bool {
        if (ninfo(other).depth >= 0)
          return false;  // Already in tree
 
        const auto &pi = ninfo(p);
        auto &oi = ninfo(other);
        oi.parent = p;
        oi.parent_arc = a;
        oi.depth = pi.depth + 1;
 
        auto src = static_cast<Node *>(a->src_node);
        if (src == p)
          {
            oi.arc_from_parent = true;
            oi.potential = pi.potential - a->cost;
          }
        else
          {
            oi.arc_from_parent = false;
            oi.potential = pi.potential + a->cost;
          }
 
        ainfo(a).state = Simplex_Arc_State::Tree;
        ++nodes_in_tree;
        queue.put(other);
        return true;
      };
 
      // Build tree with multiple priority passes
      while (not queue.is_empty() and nodes_in_tree < total_nodes)
        {
          auto p = queue.get();
 
          // Collect all candidate arcs with priorities
          struct ArcPriority {
            Arc* arc;
            Node* other;
            int priority;  // 0 = partial flow, 1 = with flow, 2 = no flow
          };
          DynList<ArcPriority> candidates;
 
          for (Node_Arc_Iterator<Net> it(p); it.has_curr(); it.next_ne())
            {
              auto a = it.get_curr();
              auto other = net.get_connected_node(a, p);
              if (ninfo(other).depth >= 0)
                continue;  // Already in tree
 
              int prio;
              if (is_partial_flow(a))
                prio = 0;  // Highest priority
              else if (a->flow > eps())
                prio = 1;  // Medium priority
              else
                prio = 2;  // Lowest priority
 
              candidates.append(ArcPriority{a, other, prio});
            }
 
          // Sort by priority (partial flow first)
          // Since DynList doesn't have sort, process in order
          for (int target_prio = 0; target_prio <= 2; ++target_prio)
            {
              for (auto& ap : candidates)
                {
                  if (ap.priority == target_prio)
                    add_to_tree(p, ap.arc, ap.other);
                }
            }
        }
 
      // Classify remaining non-tree arcs
      for (typename Net::Arc_Iterator it(net); it.has_curr(); it.next_ne())
        {
          auto a = it.get_curr();
          if (ainfo(a).state == Simplex_Arc_State::Tree)
            continue;
 
          if (a->flow <= eps())
            ainfo(a).state = Simplex_Arc_State::Lower;
          else if (a->flow >= a->cap - eps())
            ainfo(a).state = Simplex_Arc_State::Upper;
          else
            {
              // Partial flow arc NOT in tree - classify based on reduced cost
              auto rc = reduced_cost(a);
              ainfo(a).state = (rc < -eps()) ?
                  Simplex_Arc_State::Upper : Simplex_Arc_State::Lower;
            }
        }
    }
 
    Arc *find_entering_arc()
    {
      Arc *best = nullptr;
      Flow_Type best_violation = eps();  // Threshold to avoid tiny violations
      bool best_is_increase = true;
 
      for (typename Net::Arc_Iterator it(net); it.has_curr(); it.next_ne())
        {
          auto a = it.get_curr();
          auto &ai = ainfo(a);
 
          if (ai.state == Simplex_Arc_State::Tree)
            continue;
 
          if (ai.skip)  // Skip arcs that failed in this round
            continue;
 
          const auto rc = reduced_cost(a);
          const bool can_increase = (a->flow < a->cap - eps());
          const bool can_decrease = (a->flow > eps());
 
          // Check FORWARD direction: increase flow (rc < 0 is good)
          if (can_increase and rc < -best_violation)
            {
              best_violation = -rc;
              best = a;
              best_is_increase = true;
            }
 
          // Check BACKWARD direction: decrease flow (rc > 0 is good)
          // This is equivalent to using the "reverse arc" in residual network
          if (can_decrease and rc > best_violation)
            {
              best_violation = rc;
              best = a;
              best_is_increase = false;
            }
        }
 
      // Update state based on direction
      if (best != nullptr)
        {
          ainfo(best).state = best_is_increase ?
              Simplex_Arc_State::Lower : Simplex_Arc_State::Upper;
        }
 
      return best;
    }
 
    Node *find_lca(Node *u, Node *v)
    {
      ++lca_mark;  // Use new mark
 
      // Mark path from u to root
      Node *p = u;
      while (p != nullptr)
        {
          ninfo(p).mark = lca_mark;
          p = parent(p);
        }
 
      // Walk from v towards root until we hit a marked node
      p = v;
      while (p != nullptr and ninfo(p).mark != lca_mark)
        p = parent(p);
 
      return p;
    }
 
    bool augment_and_find_leaving(Arc *entering, Flow_Type &delta,
                                  Arc *&leaving, bool &leaving_goes_lower)
    {
      auto u = static_cast<Node *>(entering->src_node);
      auto v = static_cast<Node *>(entering->tgt_node);
      Node *lca = find_lca(u, v);
 
      assert(lca != nullptr);
 
      // Determine if we're increasing or decreasing flow on entering arc
      const bool increase_on_entering = (ainfo(entering).state == Simplex_Arc_State::Lower);
 
      // Count arcs in the cycle and check if it's a valid cycle
      // A valid cycle must have at least one arc where flow increases
      // and at least one where flow decreases (in the cycle direction)
      size_t arcs_with_increase = 0;
      size_t arcs_with_decrease = 0;
      size_t total_cycle_arcs = 1;  // Start with entering arc
 
      if (increase_on_entering)
        ++arcs_with_increase;
      else
        ++arcs_with_decrease;
 
 
      // Walk from u to lca and count
      Node *p = u;
      while (p != lca)
        {
          bool from_parent = ninfo(p).arc_from_parent;
          bool flow_increases = (increase_on_entering == from_parent);
 
          if (flow_increases)
            ++arcs_with_increase;
          else
            ++arcs_with_decrease;
 
          ++total_cycle_arcs;
          p = parent(p);
        }
 
      // Walk from v to lca and count
      p = v;
      while (p != lca)
        {
          bool from_parent = ninfo(p).arc_from_parent;
          bool flow_increases = (increase_on_entering != from_parent);
 
          if (flow_increases)
            ++arcs_with_increase;
          else
            ++arcs_with_decrease;
 
          ++total_cycle_arcs;
          p = parent(p);
        }
 
      // If the cycle only has one arc (the entering arc itself) or
      // all arcs go in the same direction, it's not a valid cycle
      // for flow redistribution
      if (total_cycle_arcs <= 1 or arcs_with_increase == 0 or arcs_with_decrease == 0)
        {
          delta = 0;
          leaving = entering;
          leaving_goes_lower = not increase_on_entering;
          return false;  // No valid pivot possible
        }
 
      // Initialize with entering arc's slack
      if (increase_on_entering)
        delta = entering->cap - entering->flow;
      else
        delta = entering->flow;
 
      leaving = entering;
      leaving_goes_lower = increase_on_entering;
 
      // Walk from u to lca
      // Direction: lca → ... → u (following tree direction)
      // If increase_on_entering, flow increases in arcs pointing towards u
      p = u;
      while (p != lca)
        {
          Arc *pa = parent_arc(p);
          bool from_parent = ninfo(p).arc_from_parent;
          // from_parent=true means arc goes parent→child (towards u)
          // So flow increases when both are true or both are false
          bool flow_increases = (increase_on_entering == from_parent);
 
          Flow_Type slack;
          bool goes_lower;
 
          if (flow_increases)
            {
              slack = pa->cap - pa->flow;
              goes_lower = false;
            }
          else
            {
              slack = pa->flow;
              goes_lower = true;
            }
 
          // Prefer arc that goes to lower bound in case of tie (Bland's rule variant)
          if (slack < delta or (slack == delta and goes_lower and not leaving_goes_lower))
            {
              delta = slack;
              leaving = pa;
              leaving_goes_lower = goes_lower;
            }
 
          p = parent(p);
        }
 
      // Walk from v to lca
      // Direction: v → ... → lca (against tree direction)
      // If increase_on_entering, flow decreases in arcs pointing towards v
      p = v;
      while (p != lca)
        {
          Arc *pa = parent_arc(p);
          bool from_parent = ninfo(p).arc_from_parent;
          // from_parent=true means arc goes parent→child (towards v)
          // Since we go against tree direction, flow decreases when from_parent=true
          bool flow_increases = (increase_on_entering != from_parent);
 
          Flow_Type slack;
          bool goes_lower;
 
          if (flow_increases)
            {
              slack = pa->cap - pa->flow;
              goes_lower = false;
            }
          else
            {
              slack = pa->flow;
              goes_lower = true;
            }
 
          if (slack < delta or (slack == delta and goes_lower and not leaving_goes_lower))
            {
              delta = slack;
              leaving = pa;
              leaving_goes_lower = goes_lower;
            }
 
          p = parent(p);
        }
 
      // Allow degenerate pivots (delta=0) if we found a valid leaving arc
      // This restructures the tree without changing flow, potentially enabling
      // future pivots that were previously blocked.
      if (delta >= 0 and leaving != nullptr)
        {
          // Update entering arc
          if (increase_on_entering)
            entering->flow += delta;
          else
            entering->flow -= delta;
 
          // Update u-side (same logic as above)
          p = u;
          while (p != lca)
            {
              Arc *pa = parent_arc(p);
              bool from_parent = ninfo(p).arc_from_parent;
              bool flow_increases = (increase_on_entering == from_parent);
 
              if (flow_increases)
                pa->flow += delta;
              else
                pa->flow -= delta;
 
              p = parent(p);
            }
 
          // Update v-side (same logic as above)
          p = v;
          while (p != lca)
            {
              Arc *pa = parent_arc(p);
              bool from_parent = ninfo(p).arc_from_parent;
              bool flow_increases = (increase_on_entering != from_parent);
 
              if (flow_increases)
                pa->flow += delta;
              else
                pa->flow -= delta;
 
              p = parent(p);
            }
 
          return true;  // Successful pivot (including degenerate with delta=0)
        }
 
      return false;  // Failed - no valid cycle found
    }
 
    void pivot_tree(Arc *entering, Arc *leaving, bool leaving_goes_lower)
    {
      // Handle degenerate pivot where entering = leaving
      if (entering == leaving)
        {
          auto &ai = ainfo(entering);
          ai.state = leaving_goes_lower ?
              Simplex_Arc_State::Lower : Simplex_Arc_State::Upper;
          return;
        }
 
      // Set leaving arc state
      ainfo(leaving).state = leaving_goes_lower ?
          Simplex_Arc_State::Lower : Simplex_Arc_State::Upper;
 
      // Set entering arc as tree arc
      ainfo(entering).state = Simplex_Arc_State::Tree;
 
      // Find which end of leaving arc becomes the new subtree root
      // One of the endpoints must have leaving as its parent_arc
      auto leaving_src = static_cast<Node *>(leaving->src_node);
      auto leaving_tgt = static_cast<Node *>(leaving->tgt_node);
 
      Node *subtree_root;
      bool src_has_leaving = (parent_arc(leaving_src) == leaving);
      bool tgt_has_leaving = (parent_arc(leaving_tgt) == leaving);
 
      if (not src_has_leaving and not tgt_has_leaving)
        return;  // Invalid pivot
 
      if (src_has_leaving)
        subtree_root = leaving_src;
      else
        subtree_root = leaving_tgt;
 
      auto entering_src = static_cast<Node *>(entering->src_node);
      auto entering_tgt = static_cast<Node *>(entering->tgt_node);
 
      // Determine which end of entering arc is in the subtree
      Node *in_subtree, *out_subtree;
      {
        Node *p = entering_src;
        bool src_in = false;
        while (p != nullptr)
          {
            if (p == subtree_root)
              {
                src_in = true;
                break;
              }
            p = parent(p);
          }
 
        if (src_in)
          {
            in_subtree = entering_src;
            out_subtree = entering_tgt;
          }
        else
          {
            in_subtree = entering_tgt;
            out_subtree = entering_src;
          }
      }
 
      // Reverse path from subtree_root to in_subtree
      DynList<Node *> path;
      Node *p = in_subtree;
      while (p != subtree_root and p != nullptr)
        {
          path.insert(p);  // Prepend
          p = parent(p);
        }
      if (p == subtree_root)
        path.insert(subtree_root);
      else
        return;  // in_subtree not descendant of subtree_root
 
      // Reverse parent relationships along the path
      // Path is: [subtree_root, X, Y, ..., in_subtree] (built by prepending)
      //
      // Original tree (parent pointers):
      //   in_subtree --> Y --> X --> subtree_root --> (via leaving to rest of tree)
      //   (each node's parent is to its right)
      //
      // After reversal (parent pointers):
      //   subtree_root --> X --> Y --> in_subtree --> out_subtree --> ...
      //   (each node's parent is to its right, but in_subtree connects via entering)
      //
      // For each pair (curr, next) in [subtree_root, X, Y, ...]:
      // - Original: next.parent = curr, so parent_arc(next) = arc between them
      // - New: curr.parent = next, using the same arc
      for (auto it = path.get_it(); it.has_curr(); )
        {
          Node *curr = it.get_curr();
          it.next();
 
          if (not it.has_curr())
            break;
 
          Node *next = it.get_curr();
 
          // Original: next was child of curr, so parent_arc(next) = arc between curr and next
          Arc *arc_between = parent_arc(next);
          auto &curr_info = ninfo(curr);
          curr_info.parent = next;
          curr_info.parent_arc = arc_between;
 
          auto arc_src = static_cast<Node *>(arc_between->src_node);
          curr_info.arc_from_parent = (arc_src == next);
        }
 
      // Link in_subtree to out_subtree via entering arc
      auto &sub_info = ninfo(in_subtree);
      sub_info.parent = out_subtree;
      sub_info.parent_arc = entering;
      sub_info.arc_from_parent = (static_cast<Node *>(entering->src_node) == out_subtree);
 
      // Update depths and potentials using BFS from in_subtree
      DynListQueue<Node *> queue;
      queue.put(in_subtree);
 
      auto &out_info = ninfo(out_subtree);
      sub_info.depth = out_info.depth + 1;
      if (sub_info.arc_from_parent)
        sub_info.potential = out_info.potential - entering->cost;
      else
        sub_info.potential = out_info.potential + entering->cost;
 
      while (not queue.is_empty())
        {
          Node *curr = queue.get();
          const auto &curr_info = ninfo(curr);
 
          // Find children of curr (nodes whose parent is curr)
          for (typename Net::Node_Iterator nit(net); nit.has_curr(); nit.next_ne())
            {
              Node *child = nit.get_curr();
              if (child == curr)
                continue;
 
              if (parent(child) != curr)
                continue;
 
              auto &ci = ninfo(child);
              ci.depth = curr_info.depth + 1;
 
              Arc *pa = parent_arc(child);
              if (ci.arc_from_parent)
                ci.potential = curr_info.potential - pa->cost;
              else
                ci.potential = curr_info.potential + pa->cost;
 
              queue.put(child);
            }
        }
    }
 
  public:
    explicit Network_Simplex(Net &network) : net(network) {}
 
    void set_lower_bound(Arc *a, Flow_Type lower_bound)
    {
      support_lower_bounds = true;
      ainfo(a).lower_bound = lower_bound;
    }
 
    [[nodiscard]] Flow_Type get_lower_bound(Arc *a) const
    {
      return ainfo(a).lower_bound;
    }
 
    [[nodiscard]] bool is_at_lower_bound(Arc *a) const
    {
      return std::abs(a->flow - ainfo(a).lower_bound) < eps();
    }
 
    [[nodiscard]] bool is_at_upper_bound(Arc *a) const
    {
      return std::abs(a->flow - a->cap) < eps();
    }
 
    [[nodiscard]] Flow_Type residual_capacity(Arc *a) const
    {
      return a->cap - a->flow;
    }
 
    [[nodiscard]] Flow_Type residual_lower(Arc *a) const
    {
      return a->flow - ainfo(a).lower_bound;
    }
 
 
  public:
    size_t run([[maybe_unused]] Flow_Type unused = 0)
    {
      ah_domain_error_if(not (net.is_single_source() and net.is_single_sink()))
          << "Network is not single source and single sink";
 
      stats.reset();
      auto total_start = std::chrono::high_resolution_clock::now();
 
      init_structures();
      build_spanning_tree();
 
      // Count initial partial-flow arcs
      stats.initial_partial_arcs = count_non_tree_partial_arcs();
 
      // PHASE I: Establish valid basic feasible solution
      auto phase1_start = std::chrono::high_resolution_clock::now();
      size_t phase1_pivots = force_partial_arcs_into_tree();
      auto phase1_end = std::chrono::high_resolution_clock::now();
      stats.phase1_time_ms = std::chrono::duration<double, std::milli>(
        phase1_end - phase1_start).count();
      stats.phase1_pivots = phase1_pivots;
      stats.forced_into_tree = phase1_pivots;
 
      // PHASE II: Optimize cost using standard Network Simplex
      auto phase2_start = std::chrono::high_resolution_clock::now();
      num_pivots = phase1_pivots;
      size_t failed_attempts = 0;
      const size_t max_pivots = net.vsize() * net.esize() * 10 + 1000;
      const size_t max_failures = net.esize() + 1;
 
      while (num_pivots < max_pivots and failed_attempts < max_failures)
        {
          Arc *entering = find_entering_arc();
 
          if (entering == nullptr)
            break;  // Optimal!
 
          Flow_Type delta;
          Arc *leaving;
          bool leaving_goes_lower;
 
          bool success = augment_and_find_leaving(entering, delta, leaving, leaving_goes_lower);
 
          if (success)
            {
              if (std::abs(delta) < eps())
                ++stats.degenerate_pivots;
 
              pivot_tree(entering, leaving, leaving_goes_lower);
              ++num_pivots;
              failed_attempts = 0;
 
              // Reset skip flags after successful pivot
              for (typename Net::Arc_Iterator ait(net); ait.has_curr(); ait.next_ne())
                ainfo(ait.get_curr()).skip = false;
            }
          else
            {
              ainfo(entering).skip = true;
              ++failed_attempts;
            }
        }
 
      auto phase2_end = std::chrono::high_resolution_clock::now();
      stats.phase2_time_ms = std::chrono::duration<double, std::milli>(
        phase2_end - phase2_start).count();
      stats.phase2_pivots = num_pivots - phase1_pivots;
 
      auto total_end = std::chrono::high_resolution_clock::now();
      stats.total_time_ms = std::chrono::duration<double, std::milli>(
        total_end - total_start).count();
      stats.total_pivots = num_pivots;
 
      // Count tree arcs
      stats.tree_arcs = 0;
      for (typename Net::Arc_Iterator it(net); it.has_curr(); it.next_ne())
        if (ainfo(it.get_curr()).state == Simplex_Arc_State::Tree)
          ++stats.tree_arcs;
 
      return num_pivots;
    }
 
    [[nodiscard]] size_t get_num_pivots() const { return num_pivots; }
 
    [[nodiscard]] const NetworkSimplexStats & get_stats() const noexcept { return stats; }
 
    void print_stats() const
    {
      std::cout << "=== Network Simplex Statistics ===\n"
                << "Total pivots: " << stats.total_pivots << "\n"
                << "  Phase I pivots: " << stats.phase1_pivots << "\n"
                << "  Phase II pivots: " << stats.phase2_pivots << "\n"
                << "  Degenerate pivots: " << stats.degenerate_pivots << "\n"
                << "Tree arcs: " << stats.tree_arcs << " (expected " << (net.vsize() - 1) << ")\n"
                << "Initial partial-flow arcs: " << stats.initial_partial_arcs << "\n"
                << "Arcs forced into tree: " << stats.forced_into_tree << "\n"
                << "Timing:\n"
                << "  Phase I: " << stats.phase1_time_ms << " ms\n"
                << "  Phase II: " << stats.phase2_time_ms << " ms\n"
                << "  Total: " << stats.total_time_ms << " ms\n";
    }
 
    size_t force_partial_arcs_into_tree()
    {
      size_t forced_pivots = 0;
      bool made_progress = true;
 
      while (made_progress)
        {
          made_progress = false;
 
          // Find a non-tree arc with partial flow
          for (typename Net::Arc_Iterator it(net); it.has_curr(); it.next_ne())
            {
              auto a = it.get_curr();
              if (ainfo(a).state == Simplex_Arc_State::Tree)
                continue;
 
              if (not is_partial_flow(a))
                continue;
 
              // Found a partial-flow arc not in tree - force it in
              // Mark it as Lower (to increase flow direction)
              ainfo(a).state = Simplex_Arc_State::Lower;
 
              Flow_Type delta;
              Arc *leaving;
              bool leaving_goes_lower;
 
              // Try to find a valid cycle and leaving arc
              bool success = augment_and_find_leaving(a, delta, leaving, leaving_goes_lower);
 
              if (success and leaving != nullptr and leaving != a)
                {
                  // Verify leaving arc is in tree
                  if (ainfo(leaving).state != Simplex_Arc_State::Tree)
                    {
                      ainfo(a).state = Simplex_Arc_State::Lower;
                      continue;
                    }
 
                  pivot_tree(a, leaving, leaving_goes_lower);
                  ++forced_pivots;
                  made_progress = true;
                  break;
                }
              else
                {
                  // Try the other direction (Upper = decrease flow)
                  ainfo(a).state = Simplex_Arc_State::Upper;
                  success = augment_and_find_leaving(a, delta, leaving, leaving_goes_lower);
 
                  if (success and leaving != nullptr and leaving != a)
                    {
                      pivot_tree(a, leaving, leaving_goes_lower);
                      ++forced_pivots;
                      made_progress = true;
                      break;
                    }
                  else
                    {
                      // Cannot add this arc - restore to appropriate bound
                      if (a->flow <= eps())
                        ainfo(a).state = Simplex_Arc_State::Lower;
                      else if (a->flow >= a->cap - eps())
                        ainfo(a).state = Simplex_Arc_State::Upper;
                      else
                        ainfo(a).state = Simplex_Arc_State::Lower;  // Should not happen
                    }
                }
            }
        }
 
      return forced_pivots;
    }
 
    bool is_valid_basic_solution() const
    {
      for (typename Net::Arc_Iterator it(net); it.has_curr(); it.next_ne())
        {
          auto a = it.get_curr();
          if (ainfo(a).state == Simplex_Arc_State::Tree)
            continue;
 
          // Non-tree arc must be at bounds
          if (is_partial_flow(a))
            return false;
        }
      return true;
    }
 
    size_t count_non_tree_partial_arcs() const
    {
      size_t count = 0;
      for (typename Net::Arc_Iterator it(net); it.has_curr(); it.next_ne())
        {
          auto a = it.get_curr();
          if (ainfo(a).state != Simplex_Arc_State::Tree and is_partial_flow(a))
            ++count;
        }
      return count;
    }
 
    bool verify_tree_reduced_costs() const
    {
      for (typename Net::Arc_Iterator it(net); it.has_curr(); it.next_ne())
        {
          auto a = it.get_curr();
          if (ainfo(a).state != Simplex_Arc_State::Tree)
            continue;
 
          auto rc = reduced_cost(a);
          if (std::abs(rc) > eps() * 100)  // Allow small tolerance
            return false;
        }
      return true;
    }
 
    [[nodiscard]] bool verify_tree_integrity() const
    {
      for (typename Net::Node_Iterator it(net); it.has_curr(); it.next_ne())
        {
          auto p = it.get_curr();
          if (p == root)
            continue;
 
          auto pa = parent_arc(p);
          if (pa == nullptr)
            return false;
 
          if (ainfo(pa).state != Simplex_Arc_State::Tree)
            return false;
        }
      return true;
    }
 
    void print_diagnostics() const
    {
      std::cout << "\n=== Network Simplex Diagnostics ===\n";
 
      // Count arc types
      size_t tree_arcs = 0, lower_arcs = 0, upper_arcs = 0;
      for (typename Net::Arc_Iterator it(net); it.has_curr(); it.next_ne())
        {
          switch (ainfo(it.get_curr()).state)
            {
            case Simplex_Arc_State::Tree: ++tree_arcs; break;
            case Simplex_Arc_State::Lower: ++lower_arcs; break;
            case Simplex_Arc_State::Upper: ++upper_arcs; break;
            }
        }
 
      std::cout << "Arcs: Tree=" << tree_arcs << " Lower=" << lower_arcs
                << " Upper=" << upper_arcs << " Total=" << net.esize() << "\n";
      std::cout << "Expected tree arcs: " << (net.vsize() - 1) << "\n";
 
      // Verify tree reduced costs
      bool tree_rc_ok = verify_tree_reduced_costs();
      std::cout << "Tree arcs rc=0: " << (tree_rc_ok ? "YES" : "NO") << "\n";
 
      // Check for optimality violations
      size_t violations = 0;
      for (typename Net::Arc_Iterator it(net); it.has_curr(); it.next_ne())
        {
          auto a = it.get_curr();
          auto state = ainfo(a).state;
          auto rc = reduced_cost(a);
 
          if (state == Simplex_Arc_State::Lower)
            {
              // Lower: flow=0, can increase. Optimal if rc >= 0
              if (rc < -eps() and a->flow < a->cap - eps())
                {
                  ++violations;
                  std::cout << "  VIOLATION: Lower arc with rc=" << rc
                            << " flow=" << a->flow << "/" << a->cap << "\n";
                }
            }
          else if (state == Simplex_Arc_State::Upper)
            {
              // Upper: flow=cap, can decrease. Optimal if rc <= 0
              if (rc > eps() and a->flow > eps())
                {
                  ++violations;
                  std::cout << "  VIOLATION: Upper arc with rc=" << rc
                            << " flow=" << a->flow << "/" << a->cap << "\n";
                }
            }
        }
 
      std::cout << "Optimality violations: " << violations << "\n";
      std::cout << "==================================\n";
    }
  };
 
 
  template <FlowNetwork Net,
            template <class> class Max_Flow_Algo = Ford_Fulkerson_Maximum_Flow>
  size_t max_flow_min_cost_by_network_simplex(Net & net)
  {
    Max_Flow_Algo<Net>()(net);  // First compute maximum flow
    Network_Simplex<Net> simplex(net);
    return simplex.run();
  }
 
 
  template <FlowNetwork Net,
            template <class> class Max_Flow_Algo = Ford_Fulkerson_Maximum_Flow>
  struct Max_Flow_Min_Cost_By_Network_Simplex
  {
    size_t operator ()(Net & net)
    {
      return max_flow_min_cost_by_network_simplex<Net, Max_Flow_Algo>(net);
    }
  };
 
} // end namespace Aleph
 
# endif // TPL_NETCOST_H