Description
8102年,Normalgod在GLaDOS的帮助下,研制出了传送枪。但GLaDOS想把传送枪据为己有,于是把Normalgod扔进了一间实验室。这间实验室是一棵有n个节点的树。现在Normalgod在一号节点,出口也在一号节点,但为了打开它,必须经过每一个节点按下每个节点的开关,出口才能打开。GLaDOS为了杀死Normalgod,开始在实验室里释放毒气,因此Normalgod必须尽快逃出这间实验室。
当然,Normalgod手中的传送枪是可以使用的。传送枪可以发射出两个颜色不同的传送门。Normalgod可以从其中一个传送到另一个。尽管传送枪可以在视野范围内的任何一个经过特殊处理的表面打开一扇传送门,但这间实验室的设计使得Normalgod只能在他所处的房间内打开一个传送门。 在已经存在了一个同颜色的传送门时,打开新的传送门会使与它同颜色的旧门消失。传送和打开传送门所需时间为0。
显然,利用传送枪会让Normalgod更快解决谜题,可Normalgod死在了按下最后一个按钮的路上。尽管如此,GLaDOS还是很想知道到底Normalgod最快能用多久逃出去,这对她的实验室设计方法论有重要的指导作用。作为GLaDOS的算法模块,你要完成这个任务。本题时限为2000ms
当然,Normalgod手中的传送枪是可以使用的。传送枪可以发射出两个颜色不同的传送门。Normalgod可以从其中一个传送到另一个。尽管传送枪可以在视野范围内的任何一个经过特殊处理的表面打开一扇传送门,但这间实验室的设计使得Normalgod只能在他所处的房间内打开一个传送门。 在已经存在了一个同颜色的传送门时,打开新的传送门会使与它同颜色的旧门消失。传送和打开传送门所需时间为0。
显然,利用传送枪会让Normalgod更快解决谜题,可Normalgod死在了按下最后一个按钮的路上。尽管如此,GLaDOS还是很想知道到底Normalgod最快能用多久逃出去,这对她的实验室设计方法论有重要的指导作用。作为GLaDOS的算法模块,你要完成这个任务。本题时限为2000ms
Input
第一行一个整数n。之后n-1行,每行三个整数ui,vi,ai ,表示有一条从ui 连向vi ,花费时间为ai 的通道。
Output
一行一个数T,表示最小的脱逃时间。
Sample Input
5
1 2 2
2 3 3
2 4 5
1 5 1
Sample Output
13 样例说明
1--> open1--> 5--> open2--> use(1)--> 2--> 3--> open2--> use(1)--> 2--> 4--> open2--> use(1)--> exit
Data Constraint
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" alt=" " />
题解(摘自JZOJ):
1.易知:每条边至多经过2次。
2.那么最长距离总权值*2,那么我们只需要使经过一次的边的总和更大,
则长度=总权值*2-选用的单边权值之和。
3.由此我们可以采用动态规划来求解。
dp[i][0/1]
0表示在i点及i点儿子设传送门所能得到的最大总和
1 表示不在i点及i点儿子设传送门所能得到的最大总和
首先,对于dp[i][1]的情况,一定存在i点的祖先中有传送门,这样才能使结果更优。所以对于他的每一个儿子都能跳回到他的祖先。但实际上只有使一个儿子跳回祖先时,才能保证fa->i的边经过两次。
否则转化为dp[i][0]的情况。则我们要使选的儿子最优。
dp[i][1]=max(dp[vi][1]+wi);
其次,对于dp[i][0]的情况,在每个儿子中设立传送门并不会影响到其他儿子,因为总能从儿子回到i时再在i重设传送门。所以我们就取每个儿子设与不设的最优值之和。
dp[i][0]=max(dp[vi][0],dp[vi][1]+wi);
#include <cstring>
#include <iostream>
#include <cstdio>
#define N 1000007
#define LL long long
using namespace std;
int n,ls[N],tot;
struct edge{
int to,next;
LL val;
}e[N*];
LL ans,f[N][]; void Add(int x,int y,LL z){
e[++tot].to=y;
e[tot].next=ls[x];
e[tot].val=z;
ls[x]=tot;
} void Dfs(int x,int pre){
for (int i=ls[x];i;i=e[i].next){
int v=e[i].to;
if (v==pre) continue;
Dfs(v,x);
f[x][]=max(f[x][],f[v][]+e[i].val);
f[x][]+=max(f[v][],f[v][]+e[i].val);
}
} void Init(){
scanf("%d",&n);
for (int i=;i<n;i++){
int u,v;
LL w;
scanf("%d%d%lld",&u,&v,&w);
ans+=*w;
Add(u,v,w);
Add(v,u,w);
}
} int main(){
freopen("portal.in","r",stdin);
freopen("portal.out","w",stdout);
Init();
Dfs(,);
ans-=max(f[][],f[][]);
printf("%lld",ans);
}