Description
Given an undirected weighted graph G, you should find one of spanning trees specified as follows.
The graph G is an ordered pair (V, E), where V is a set of vertices {v1,
v2, …, vn} and E is a set of undirected edges {e1,
e2, …, em}. Each edge e ∈ E has its weight
w(e).
A spanning tree T is a tree (a connected subgraph without cycles) which connects all the n vertices with
n ? 1 edges. The slimness of a spanning tree T is defined as the difference between the largest weight and the smallest weight among the
n ? 1 edges of T.
Figure 5: A graph G and the weights of the edges
For example, a graph G in Figure 5(a) has four vertices {v1,
v2, v3, v4} and five undirected edges {e1,
e2, e3, e4, e5}. The weights of the edges are
w(e1) = 3, w(e2) = 5,
w(e3) = 6, w(e4) = 6, w(e5) = 7 as shown in Figure 5(b).
Figure 6: Examples of the spanning trees of G
There are several spanning trees for G. Four of them are depicted in Figure 6(a)~(d). The spanning tree
Ta in Figure 6(a) has three edges whose weights are 3, 6 and 7. The largest weight is 7 and the smallest weight is 3 so that the slimness of the tree
Ta is 4. The slimnesses of spanning trees Tb,
Tc and Td shown in Figure 6(b), (c) and (d) are 3, 2 and 1, respectively. You can easily see the slimness of any other spanning tree is greater than or equal to 1, thus the spanning tree Td in Figure 6(d) is one of the
slimmest spanning trees whose slimness is 1.
Your job is to write a program that computes the smallest slimness.
Input
The input consists of multiple datasets, followed by a line containing two zeros separated by a space. Each dataset has the following format.
| n | m | |
| a1 | b1 | w1 |
| ? | ||
| am | bm | wm |
Every input item in a dataset is a non-negative integer. Items in a line are separated by a space. n is the number of the vertices and m the number of the edges. You can assume 2 ≤
n ≤ 100 and 0 ≤ m ≤ n(n ? 1)/2. ak and
bk (k = 1, …, m) are positive integers less than or equal to
n, which represent the two vertices vak and
vbk connected by the kth edge ek.
wk is a positive integer less than or equal to 10000, which indicates the weight of
ek. You can assume that the graph G = (V,
E) is simple, that is, there are no self-loops (that connect the same vertex) nor parallel edges (that are two or more edges whose both ends are the same two vertices).
Output
For each dataset, if the graph has spanning trees, the smallest slimness among them should be printed. Otherwise, ?1 should be printed. An output should not contain extra characters.
Sample Input
4 5 1 2 3 1 3 5 1 4 6 2 4 6 3 4 7 4 6 1 2 10 1 3 100 1 4 90 2 3 20 2 4 80 3 4 40 2 1 1 2 1 3 0 3 1 1 2 1 3 3 1 2 2 2 3 5 1 3 6 5 10 1 2 110 1 3 120 1 4 130 1 5 120 2 3 110 2 4 120 2 5 130 3 4 120 3 5 110 4 5 120 5 10 1 2 9384 1 3 887 1 4 2778 1 5 6916 2 3 7794 2 4 8336 2 5 5387 3 4 493 3 5 6650 4 5 1422 5 8 1 2 1 2 3 100 3 4 100 4 5 100 1 5 50 2 5 50 3 5 50 4 1 150 0 0
Sample Output
1 20 0 -1 -1 1 0 1686 50
题意：求最小生成树最大边和最小边的最小差值
思路：kruskal排序后每次第一个选的和最后一个选的就是差值，找到最小的
#include <iostream>
#include <cstdio>
#include <cstring>
#include <algorithm>
#include <queue>
using namespace std;
const int maxn = 110;
const int inf = 0x3f3f3f3f;
struct Edge {
int from, to, dist;
} edge[maxn*maxn];
int n, m;
int ans, fa[maxn];
int cmp(Edge a, Edge b) {
return a.dist < b.dist;
}
void init() {
for (int i = 1; i <= n; i++)
fa[i] = i;
}
int find(int x) {
if (x != fa[x])
fa[x] = find(fa[x]);
return fa[x];
}
void kruskal() {
ans = inf;
sort(edge, edge+m, cmp);
for (int i = 0; i < m; i++) {
init();
int cnt = 0, tmp = inf;
for (int j = i; j < m; j++) {
int fx = find(edge[j].from);
int fy = find(edge[j].to);
if (fx != fy) {
fa[fx] = fy;
cnt++;
if (cnt == n-1) {
tmp = edge[j].dist - edge[i].dist;
break;
}
}
}
if (tmp < ans)
ans = tmp;
}
}
int main() {
while (scanf("%d%d", &n, &m) != EOF && n+m) {
for (int i = 0; i < m; i++)
scanf("%d%d%d", &edge[i].from, &edge[i].to, &edge[i].dist);
kruskal();
if (ans == inf)
printf("-1\n");
else printf("%d\n", ans);
}
return 0;
}