对顶点和边列表使用 listS 时无法调用 boost::clear_vertex

Question

我正在编写一个程序，该程序使用 boost 图形库来解决旅行商问题，该问题使用 A* 搜索和最小生成树启发式算法。我对 boost::graph 很陌生 在我的启发式课程中，我计算了所有尚未访问的顶点的最小生成树。我通过维护一个来跟踪访问了哪些顶点 原始图的副本，我在每次调用启发式时从中删除当前顶点及其所有边。但是，当我调用 boost::clear_vertex(u, subGraph) 时，u 是 vertex_descriptor 和 subGraph 是我从中减去顶点的原始图的副本，我得到一个调试断言失败说明：

列出擦除迭代器超出范围。

经过一些调试，我发现最终在 STL <list> 的第 1383 行产生了错误，由于某种原因，以下条件为 false：

_Where._Getcont() != _STD addressof(this->_Get_data()).

这是我的启发式课程：

class MST_Heuristic : public astar_heuristic<MyGraphType, double>
{
public:
    MST_Heuristic(vertex_descriptor goal, MyGraphType g)
        : m_goal(goal), subGraph(g), firstRun(true) {}
    double operator () (vertex_descriptor u)
    {
        double MSTDist = 0.0;
        double startDist = numeric_limits<double>::infinity();
        int minEdgeWeight = subGraph[*out_edges(u, subGraph).first].weight;         // initialize minEdgeWeight to weight of first out edge

        if (firstRun)
        {
            IndexMap mapIndex;
            associative_property_map<IndexMap> vertexIndices(mapIndex);
            int j = 0;
            for (auto v = vertices(subGraph).first; v != vertices(subGraph).second; v++)
            {
                put(vertexIndices, *v, j++);
            }

            dijkstra_shortest_paths(subGraph, u, get(&VertexData::pred, subGraph),  // calculate the shortest path from the start for each vertex
                get(&VertexData::dist2, subGraph), get(&EdgeData::weight, subGraph),
                vertexIndices, less<double>(), plus<double>(),
                numeric_limits<double>::infinity(), 0, do_nothing_dijkstra_visitor(),
                get(&VertexData::color, subGraph));
        }
        for (auto ed : make_iterator_range(out_edges(u, subGraph)))
        {
            minEdgeWeight = min(subGraph[ed].weight, minEdgeWeight);                // find distance from nearest unvisited vertex to the current vertex
        }
        clear_vertex(u, subGraph);
        remove_vertex(u, subGraph);
        // Problem here; The problem has to do with removing vertices/edges and destabilizing the graph, thereby making it impossible to iterate through the graph

        IndexMap mapIndex;
        associative_property_map<IndexMap> vertexIndices(mapIndex);
        int j = 0;
        for (auto v = vertices(subGraph).first; v != vertices(subGraph).second; v++)
        {
            put(vertexIndices, *v, j++);
        }

        prim_minimum_spanning_tree(subGraph, *vertices(subGraph).first,             // calculate the minimum spanning tree
            get(&VertexData::pred, subGraph), get(&VertexData::dist, subGraph),
            get(&EdgeData::weight, subGraph), vertexIndices,
            do_nothing_dijkstra_visitor());

        for (auto vd : make_iterator_range(vertices(subGraph)))                     // estimate distance to travel all the unvisited vertices
        {
            MSTDist += subGraph[vd].dist;
            startDist = min(startDist, subGraph[vd].dist2);
        }

        firstRun = false;
        return static_cast<double>(minEdgeWeight) + MSTDist + startDist;            // return the result of the heuristic function
    }
private:
    vertex_descriptor m_goal;
    MyGraphType subGraph;
    bool firstRun;
};

以下是一些相关的 typedef：

typedef adjacency_list_traits<listS, listS, undirectedS> GraphTraits;               // to simplify the next definition

typedef GraphTraits::vertex_descriptor vertex_descriptor;                           // vertex descriptor for the graph

typedef GraphTraits::edge_descriptor edge_descriptor;                               // edge descriptor for the graph

typedef std::map<vertex_descriptor, size_t>IndexMap;                                // type used for the vertex index property map

typedef adjacency_list<listS, listS, undirectedS,VertexData, EdgeData> MyGraphType; // graph type

我非常感谢有人为我澄清为什么会发生这种情况。此外，我对启发式类的想法可能是完全愚蠢的，所以如果你认为我应该尝试一些其他方法来实现最小生成树启发式而不是继续搞乱这个，我当然愿意接受这个前景。如果我的启发式是愚蠢的，我真的很感激一些关于还能做什么的建议。我的 boost 版本是 boost_1_67_0，我使用的是 MS Visual Studio 2017。

Answer 1

您遇到了来自 MSVC 的迭代器调试检查。这很好，因为否则您可能不知道它，您的程序会（静默？）Undefined Behaviour。

现在让我看看代码。

这看起来很可疑：

double minEdgeWeight =
    subGraph[*out_edges(u, subGraph).first].weight; // initialize minEdgeWeight to weight of first out edge

这带有一个隐含的假设，即u 至少有一个出边。这可能是真的，但你真的应该检查一下。

进一步inspection with UbSan:

/home/sehe/custom/boost_1_67_0/boost/graph/breadth_first_search.hpp:82:30: runtime error: load of value 3200171710, which is not a valid value for type 'boost::default_color_type'
SUMMARY: UndefinedBehaviorSanitizer: undefined-behavior /home/sehe/custom/boost_1_67_0/boost/graph/breadth_first_search.hpp:82:30 in 
/home/sehe/custom/boost_1_67_0/boost/graph/breadth_first_search.hpp:83:13: runtime error: load of value 3200171710, which is not a valid value for type 'ColorValue' (aka 'boost::default_color_type')
SUMMARY: UndefinedBehaviorSanitizer: undefined-behavior /home/sehe/custom/boost_1_67_0/boost/graph/breadth_first_search.hpp:83:13 in 
/home/sehe/custom/boost_1_67_0/boost/graph/breadth_first_search.hpp:87:15: runtime error: load of value 3200171710, which is not a valid value for type 'ColorValue' (aka 'boost::default_color_type')
SUMMARY: UndefinedBehaviorSanitizer: undefined-behavior /home/sehe/custom/boost_1_67_0/boost/graph/breadth_first_search.hpp:87:15 in 
sotest: /home/sehe/custom/boost_1_67_0/boost/graph/two_bit_color_map.hpp:86: void boost::put(const two_bit_color_map<IndexMap> &, typename property_traits<IndexMap>::key_type, boost::two_bit_color_type) [IndexMap = boost::associative_property_map<std::map<void *, unsigned long, std::less<void *>, std::allocator<std::pair<void *const, unsigned long> > > >]: Assertion `(std::size_t)i < pm.n' failed.

也许初始化那个颜色图是个好主意。我不知道这是否适用于您的代码，因为您没有包含相关代码 (again)。

所以我改变了：

struct VertexData {
    vertex_descriptor pred;
    double dist = 0, dist2 = 0;
    boost::default_color_type color = {};
};

不，仍然是同样的错误。现在通读代码。

... 20 分钟后。啊哈。您正在将图表复制到subGraph。但是，您还传递了一个参数u。这怎么可能是正确的？顶点u 很可能不来自subGraph。这可能是另一个错误来源。

让我们也解决这个问题：

msth(msth.vertex(2));

使用新成员访问器：

vertex_descriptor vertex(std::size_t n) const {
    return boost::vertex(n, subGraph);
}

收到您的评论

    // Problem here; The problem has to do with removing vertices/edges and destabilizing the graph, thereby making
    // it impossible to iterate through the graph

很明显，您在图形外部有一个顶点u。与“不稳定”无关（这不是它的工作原理。迭代器有时会失效，但不会因此而变得不稳定：如果不小心，您可能会调用未定义的行为）。

至少，当通过有效的u 时，UbSan 和 ASan 不会在这里抱怨，这是一个好兆头。很可能您的编译器的调试迭代器也不会抱怨。

现在，请注意：

• listS 确实 不 使 remove 上的任何其他迭代器无效（这也在 Iterator invalidation rules 中）。显然，只有那一个被移除了。

• m_goal 遇到与u 相同的问题：它几乎不可能来自正确的图表，因为您要复制整个图表

• 尽管remove 仅使特定的顶点描述符无效，但您似乎正试图在 A* 搜索的回调中执行此操作。这很可能会破坏该算法假定的不变量（我没有检查文档，但你应该检查！再次，这是因为你没有显示 A* 相关代码）。

• 对于Weight 是否为double，您的代码似乎仍然存在问题。 （为什么是static_cast？）

---

最终结果

这就是我最后得到的，包括各种清理。

Live On Coliru

#include <boost/graph/adjacency_list.hpp>
#include <boost/graph/astar_search.hpp>
#include <boost/graph/visitors.hpp>
#include <boost/graph/dijkstra_shortest_paths.hpp>
#include <boost/graph/prim_minimum_spanning_tree.hpp>
#include <boost/graph/graph_utility.hpp>
#include <iomanip>
#include <numeric>

typedef boost::adjacency_list_traits<boost::listS, boost::listS, boost::undirectedS>
    GraphTraits;                                          // to simplify the next definition
typedef GraphTraits::vertex_descriptor vertex_descriptor; // vertex descriptor for the graph
typedef GraphTraits::edge_descriptor edge_descriptor;     // edge descriptor for the graph
typedef double Weight;

struct VertexData {
    std::string name;
    VertexData(std::string name = "") : name(std::move(name)) {}
    //
    vertex_descriptor pred {};
    Weight dist = 0, dist2 = 0;
    boost::default_color_type color = {};

    friend std::ostream& operator<<(std::ostream &os, VertexData const &vd) {
        return os << "{name:" << std::quoted(vd.name) << "}";
    }
};

struct EdgeData {
    Weight weight = 1;
};

typedef boost::adjacency_list<boost::listS, boost::listS, boost::undirectedS, VertexData, EdgeData>
    MyGraphType; // graph type

class MST_Heuristic : public boost::astar_heuristic<MyGraphType, Weight> {
    struct do_nothing_dijkstra_visitor : boost::default_dijkstra_visitor {};

    auto make_index() const {
        std::map<vertex_descriptor, size_t> m;
        size_t n=0;
        for (auto vd : boost::make_iterator_range(vertices(subGraph)))
            m[vd] = n++;
        return m;
    }
  public:
    MST_Heuristic(MyGraphType g) : subGraph(g), firstRun(true) {}

    Weight operator()(vertex_descriptor u) {

        if (firstRun) {
            auto idx = make_index();
            dijkstra_shortest_paths(
                subGraph, u,
                get(&VertexData::pred, subGraph), // calculate the shortest path from the start for each vertex
                get(&VertexData::dist2, subGraph),
                get(&EdgeData::weight, subGraph),
                boost::make_assoc_property_map(idx), std::less<Weight>(),
                std::plus<Weight>(), std::numeric_limits<Weight>::infinity(), 0, do_nothing_dijkstra_visitor(),
                get(&VertexData::color, subGraph));
        }

        Weight minEdgeWeight = std::numeric_limits<Weight>::max(); // initialize minEdgeWeight to weight of first out edge
        for (auto ed : make_iterator_range(out_edges(u, subGraph))) {
            minEdgeWeight = std::min(subGraph[ed].weight, minEdgeWeight); // find distance from nearest unvisited vertex to the current vertex
        }

        clear_vertex(u, subGraph);
        remove_vertex(u, subGraph);

        {
            auto idx = make_index();
            prim_minimum_spanning_tree(subGraph, vertex(0), // calculate the minimum spanning tree
                                       get(&VertexData::pred, subGraph), get(&VertexData::dist, subGraph),
                                       get(&EdgeData::weight, subGraph), boost::make_assoc_property_map(idx),
                                       do_nothing_dijkstra_visitor());
        }

        //// combine
        Weight MSTDist = 0.0;
        Weight startDist = std::numeric_limits<Weight>::infinity();

        for (auto vd : boost::make_iterator_range(vertices(subGraph))) // estimate distance to travel all the unvisited vertices
        {
            MSTDist += subGraph[vd].dist;
            startDist = std::min(startDist, subGraph[vd].dist2);
        }

        firstRun = false;
        return minEdgeWeight + MSTDist + startDist; // return the result of the heuristic function
    }

    vertex_descriptor vertex(std::size_t n) const {
        return boost::vertex(n, subGraph);
    }

  private:

    MyGraphType subGraph;
    bool firstRun;
};

int main() {
    MyGraphType g;

    auto v1 = add_vertex({"one"}, g);
    auto v2 = add_vertex({"two"}, g);
    auto v3 = add_vertex({"three"}, g);
    auto v4 = add_vertex({"four"}, g);
    auto v5 = add_vertex({"five"}, g);

    add_edge(v1, v2, g);
    add_edge(v2, v3, g);
    add_edge(v3, v4, g);
    add_edge(v4, v5, g);

    print_graph(g, get(&VertexData::name, g));

    MST_Heuristic msth(g);
    msth(msth.vertex(2));
}

打印

one <--> two 
two <--> one three 
three <--> two four 
four <--> three five 
five <--> four