如何在 Boost Dijkstra 中定义自定义距离

How do I define a custom distance in Boost Dijkstra?

本文关键字：定义 自定义 距离 Dijkstra Boost      更新时间：2023-10-16

我目前正在查看 Boost Dijkstra 的文档 - http://www.boost.org/doc/libs/1_52_0/libs/graph/doc/dijkstra_shortest_paths.html; 我的目标是在计算距离时修改距离组合以获得"最大值"而不是"加号"。文档是这样说的：

IN: distance_combine(CombineFunction cmb)
This function is used to combine distances to compute the distance of a path. The
CombineFunction type must be a model of Binary Function. The first argument typ
of the binary function must match the value type of the DistanceMap property map
and the second argument type must match the value type of the WeightMap property
map. The result type must be the same type as the distance value type.
Default: closed_plus<D> with D=typename property_traits<DistanceMap>::value_type

定义这样一个组合函数的语法是什么？我尝试过摸索 std：：max，但我的编译器似乎对它不满意。

我打算采用懒惰的方式，只给出一些代码来展示如何做到这一点:)

#include <boost/graph/dijkstra_shortest_paths.hpp>
#include <boost/graph/adjacency_list.hpp>
struct Edge {
        Edge(float weight_) : weight(weight_) {}
        float weight;
};
// simple function
float combine(float a, float b){
        return std::max(a, b);
}
// functor
struct Combine{
        // Some internal state
        float operator()(float a, float b) const {
                return std::max(a, b);
        }
};
int main(int, char**){
        typedef boost::adjacency_list < boost::vecS, boost::vecS, boost::directedS, boost::no_property, Edge > graph_t;
        typedef boost::graph_traits < graph_t >::vertex_descriptor vertex_t;
        graph_t g;
        vertex_t a = boost::add_vertex(g);
        vertex_t b = boost::add_vertex(g);
        vertex_t c = boost::add_vertex(g);
        vertex_t d = boost::add_vertex(g);
        boost::add_edge(a, b, Edge(3), g);
        boost::add_edge(b, c, Edge(3), g);
        boost::add_edge(a, d, Edge(1), g);
        boost::add_edge(d, c, Edge(4), g);
        std::vector<vertex_t> preds(4);
        // Traditional dijsktra (sum)
        boost::dijkstra_shortest_paths(g, a, boost::predecessor_map(&preds[0]).weight_map(boost::get(&Edge::weight,g)));
        assert(preds[c] == d);
        assert(preds[d] == a);
        // Dijkstra with custom combine as a function
        boost::dijkstra_shortest_paths(g, a, boost::predecessor_map(&preds[0]).weight_map(boost::get(&Edge::weight,g)).distance_combine(&combine));
        assert(preds[c] == b);
        assert(preds[b] == a);
        // Dijkstra with custom combine as a functior
        boost::dijkstra_shortest_paths(g, a, boost::predecessor_map(&preds[0]).weight_map(boost::get(&Edge::weight,g)).distance_combine(Combine()));
        // Dijkstra with custom combine as a lambda
        boost::dijkstra_shortest_paths(g, a, boost::predecessor_map(&preds[0]).weight_map(boost::get(&Edge::weight,g)).distance_combine([](float a, float b){return std::max(a,b);}));
        return 0;
}

可能将其参数作为模板可能会使事情变得有点困难......

尝试（其中 T 是距离的类型）

T comb(T& a, T& b) { return std::max(a, b); }

并通过梳子。

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