标签：判断   EAP   done   优先队列   思想   最小   while   sizeof   三种方式   

求1-n最长边最小的路径。

最短路变形。dis值向后延申的方式是：\[dis[j]=min(dis[j],max(dis[i],w(i,j))\]

显然满足dijkstra贪心的选择方式。spfa也当然可以用。

写上三种方式，就当是模板好了。

spfa

复杂度：\(O(kE)/O(VE)\)

spfa的主要思想是不断松弛。注意spfa的更新策略，先更新\(dis\)值，再根据\(vis\)判断是否丢到\(queue\)中。

#include <bits/stdc++.h>
const int maxn = 100000;
const int maxm = 200000;

using namespace std;

int n, m;

int to[maxm * 2 + 10];
int w[maxm * 2 + 10];
int nex[maxm * 2 + 10];
int head[maxn + 10], cnt = 0;

void addEdge(int a, int b, int c)
{
    to[cnt] = b; w[cnt] = c;
    nex[cnt] = head[a]; head[a] = cnt++;
    to[cnt] = a; w[cnt] = c;
    nex[cnt] = head[b]; head[b] = cnt++;
}

int vis[maxn + 10];
int dis[maxn + 10];

void spfa()
{
    queue<int> q;
    dis[1] = 0;
    q.push(1);
    vis[1] = 1;
    while (!q.empty())
    {
        int x = q.front(); q.pop();
        vis[x] = 0;
        // printf("current node: %d %d\n", x, dis[x]);
        for (int i = head[x]; i != -1; i = nex[i])
        {
            int l = to[i];
            if (max(dis[x], w[i]) < dis[l])
            {
                dis[l] = max(dis[x], w[i]);
                if (!vis[l])
                {
                    q.push(l);
                    vis[l] = 1;
                }
            }
        }
    }
}

int main()
{
    scanf("%d%d", &n, &m);

    memset(head, -1, sizeof(head));
    for (int i = 1, a, b, c; i <= m; i++)
    {
        scanf("%d%d%d", &a, &b, &c);
        addEdge(a, b, c);
    }

    memset(vis, 0, sizeof(vis));
    memset(dis, 0x3f, sizeof(dis));

    spfa();

    printf("%d\n", dis[n]);

    return 0;
}

dijkstra

会超时。

复杂度：\(O(V^2)\)

dijkstra的主要思想是一共\(V\)次贪心的选择当前未确定点中\(dis\)值最小的那一个确定。

#include <bits/stdc++.h>
const int inf = 0x3f3f3f3f;
const int maxn = 100000;
const int maxm = 200000;

using namespace std;

int n, m;

int to[maxm * 2 + 10];
int w[maxm * 2 + 10];
int nex[maxm * 2 + 10];
int head[maxn + 10], cnt = 0;

void addEdge(int a, int b, int c)
{
    to[cnt] = b; w[cnt] = c;
    nex[cnt] = head[a]; head[a] = cnt++;
    to[cnt] = a; w[cnt] = c;
    nex[cnt] = head[b]; head[b] = cnt++;
}

int done[maxn + 10];
int dis[maxn + 10];

void dijkstra()
{
    dis[1] = 0;
    for (int i = 1; i <= n; i++)
    {
        int x = 0, mmin = inf;
        for (int j = 1; j <= n; j++)
        {
            if (!done[j] && dis[j] < mmin)
                mmin = dis[x = j];
        }
        done[x] = 1;
        for (int j = head[x]; j != -1; j = nex[j])
        {
            int l = to[j];
            dis[l] = min(dis[l], max(dis[x], w[j]));
        }
    }
}

int main()
{
    scanf("%d%d", &n, &m);

    memset(head, -1, sizeof(head));
    for (int i = 1, a, b, c; i <= m; i++)
    {
        scanf("%d%d%d", &a, &b, &c);
        addEdge(a, b, c);
    }

    memset(done, 0, sizeof(done));
    memset(dis, 0x3f, sizeof(dis));

    dijkstra();

    printf("%d\n", dis[n]);

    return 0;
}

heap_dijkstra

复杂度（stl优先队列实现，由于每条边最多被访问一次，堆中最多会有\(E\)个节点）：\(O(ElogE)\)，当图趋于完全图时，复杂度趋于\(O(V^2logV)\)，应当使用一般实现的dijkstra算法。

堆优化dijkstra，主要思想是利用堆加速每一次值最小（未确定）的点的选择。实际实现略有不同，所以复杂度并非\(O(VlogV)\)。

#include <bits/stdc++.h>
const int inf = 0x3f3f3f3f;
const int maxn = 100000;
const int maxm = 200000;

using namespace std;

int n, m;

int to[maxm * 2 + 10];
int w[maxm * 2 + 10];
int nex[maxm * 2 + 10];
int head[maxn + 10], cnt = 0;

void addEdge(int a, int b, int c)
{
    to[cnt] = b; w[cnt] = c;
    nex[cnt] = head[a]; head[a] = cnt++;
    to[cnt] = a; w[cnt] = c;
    nex[cnt] = head[b]; head[b] = cnt++;
}

struct tNode
{
    int d, u; // estimated dis, id of vertex
    tNode(int dd, int uu): d(dd), u(uu){}
    bool operator < (const tNode &y) const
    {
        return d > y.d;
    }
};

int done[maxn + 10];
int dis[maxn + 10];

void heap_dijkstra()
{
    priority_queue<tNode> q;
    dis[1] = 0;
    q.push(tNode(0, 1));
    while (!q.empty())
    {
        tNode x = q.top(); q.pop();
        int u = x.u;
        if (done[u])
            continue;
        done[u] = 1;
        for (int i = head[u]; i != -1; i = nex[i])
        {
            int l = to[i];
            if (dis[l] > max(dis[u], w[i]))
            {
                dis[l] = max(dis[u], w[i]);
                q.push(tNode(dis[l], l));
            }
        }
    }
}

int main()
{
    scanf("%d%d", &n, &m);

    memset(head, -1, sizeof(head));
    for (int i = 1, a, b, c; i <= m; i++)
    {
        scanf("%d%d%d", &a, &b, &c);
        addEdge(a, b, c);
    }

    memset(done, 0, sizeof(done));
    memset(dis, 0x3f, sizeof(dis));

    heap_dijkstra();

    printf("%d\n", dis[n]);

    return 0;
}

CCF-CSP题解 201703-4 地铁修建

标签：判断   EAP   done   优先队列   思想   最小   while   sizeof   三种方式   

原文地址：https://www.cnblogs.com/acboyty/p/11378726.html