我正在编写一个程序，该程序使用增强图谱库以最小的生成树启发式算法通过A *搜索来解决Traveling Salesman问题。我很新来提升:: graph
在启发式类中，我计算所有尚未访问的顶点的最小生成树。我通过保持一个顶点来跟踪访问过哪些顶点
原始图的副本，在每次调用启发式方法时，都会从中删除当前顶点及其所有边。但是，当我去调用boost::clear_vertex(u, subGraph)时，其中u是vertex_descriptor，而subGraph是要从中减去顶点的原始图的副本，我得到了一个调试断言失败说明：
列表擦除迭代器超出范围。
进行一些调试之后，我发现错误最终是在STL <list>的第1383行上生成的，出于某些原因，以下条件为假：
_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
我真的很感谢有人为我弄清楚为什么会这样。另外，可能我对启发式课程的想法完全是愚蠢的，因此，如果您认为我应该尝试使用其他方法来生成最小生成树启发式而不是继续对此进行弄乱，那么我肯定对潜在客户持开放态度。如果我的启发式方法很愚蠢，那么我真的很乐意就其他方法提出一些建议。我的增强版本是boost_1_67_0，我正在使用MS Visual Studio 2017。
答案 0 :(得分：2)
您正在通过MSVC进行迭代器调试检查。那很好，因为否则您可能不知道它，并且您的程序会（无声）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
这暗含了一个假设，即u至少有一个输出边缘。这可能是正确的，但您应该真正检查一下。
/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.
初始化颜色表也许是个好主意。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 = {};
};
不是，还是一样的错误。立即阅读代码。
... 20分钟后。啊哈您要将图形复制到subGraph中。但是，您还要传入参数u。那怎么可能是正确的？顶点u很可能不是来自subGraph。这可能是另一个错误来源。
我们也解决此问题：
msth(msth.vertex(2));
使用新的成员访问器：
vertex_descriptor vertex(std::size_t n) const {
return boost::vertex(n, subGraph);
}
发表评论
// 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，您从图形外部获得了一个顶点u。没什么关于“破坏稳定”的（这不是它的工作方式。迭代器有时会失效，但是没有任何事情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，当传递有效的u时，UbSan和ASan不会在这里抱怨，这是一个好兆头。您的编译器的Debug Iterators很可能也不会抱怨。
现在，请注意：
listS不会不会使remove（也在Iterator invalidation rules中）上的任何其他迭代器无效。显然，只有一个被移除了。
m_goal遇到与u相同的问题：由于您要复制整个图，因此很难从正确的图中显示
即使remove仅使特定的顶点描述符无效，但似乎您正在尝试在A *搜索的回调中执行此操作。可能会破坏该算法假定的不变式（我没有检查过文档，但是您应该！同样，这是因为您没有显示与A *相关的代码）。
您的代码似乎仍然因Weight是否为double而破损。 （为什么使用static_cast？）
这是我最后得到的，包括各种清理工作。
#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