uva 1025 A Spy in the Metro 解题报告

本文介绍了一个关于算法竞赛的问题“ASpyintheMetro”,讲述了特工Maria如何利用最优列车时刻表抵达目的地的故事,并提供了详细的算法实现过程,通过动态规划解决等待时间最小化问题。
A Spy in the Metro
Time Limit: 3000MS  64bit IO Format: %lld & %llu

 Status uDebug

  Secret agent Maria was sent to Algorithms City to carry out an especially dangerous mission. After several thrilling events we find her in the first station of Algorithms City Metro, examining the time table. The Algorithms City Metro consists of a single line with trains running both ways, so its time table is not complicated.

  Maria has an appointment with a local spy at the last station of Algorithms City Metro. Maria knows that a powerful organization is after her. She also knows that while waiting at a station, she is at great risk of being caught. To hide in a running train is much safer, so she decides to stay in running trains as much as possible, even if this means traveling backward and forward. Maria needs to know a schedule with minimal waiting time at the stations that gets her to the last station in time for her appointment. You must write a program that finds the total waiting time in a best schedule for Maria.

The Algorithms City Metro system has N stations, consecutively numbered from 1 to N. Trains move in both directions: from the first station to the last station and from the last station back to the first station. The time required for a train to travel between two consecutive stations is fixed since all trains move at the same speed. Trains make a very short stop at each station, which you can ignore for simplicity. Since she is a very fast agent, Maria can always change trains at a station even if the trains involved stop in that station at the same time.

Input

The input file contains several test cases. Each test case consists of seven lines with information as follows.

Line 1. The integer N (2 ≤ N ≤ 50), which is the number of stations.

Line 2. The integer T (0 ≤ T ≤ 200), which is the time of the appointment.

Line 3. N − 1 integers: t1, t2, . . . , tN−1 (1 ≤ ti ≤ 20), representing the travel times for the trains between two consecutive stations: t1 represents the travel time between the first two stations, t2 the time between the second and the third station, and so on.

Line 4. The integer M1 (1 ≤ M1 ≤ 50), representing the number of trains departing from the first station.

Line 5. M1 integers: d1, d2, . . . , dM1 (0 ≤ di ≤ 250 and di < di+1), representing the times at which trains depart from the first station.

Line 6. The integer M2 (1 ≤ M2 ≤ 50), representing the number of trains departing from the N-th station.

Line 7. M2 integers: e1, e2, . . . , eM2 (0 ≤ ei ≤ 250 and ei < ei+1) representing the times at which trains depart from the N-th station.

The last case is followed by a line containing a single zero.

Output

For each test case, print a line containing the case number (starting with 1) and an integer representing the total waiting time in the stations for a best schedule, or the word ‘impossible’ in case Maria is unable to make the appointment. Use the format of the sample output.

Sample Input

 

4
55
5 10 15
4
0 5 10 20
4
0 5 10 15
4
18
1 2 3
5
0 3 6 10 12
6
0 3 5 7 12 15
2
30
20
1
20
7
1 3 5 7 11 13 17
0

Sample Output

Case Number 1: 5

Case Number 2: 0

Case Number 3: impossible

 

——————————————————我是分割线————————————————————

DP水题。

  1 #include<iostream>
  2 #include<cstdio>
  3 #include<cstring>
  4 #include<cmath>
  5 #include<algorithm>
  6 #include<queue>
  7 #include<cstdlib>
  8 #include<iomanip>
  9 #include<cassert>
 10 #include<climits>
 11 #include<functional>
 12 #include<bitset>
 13 #include<vector>
 14 #include<list>
 15 #define maxn 51
 16 #define F(i,j,k) for(int i=j;i<=k;i++)
 17 #define M(a,b) memset(a,b,sizeof(a))
 18 #define FF(i,j,k) for(int i=j;i>=k;i--)
 19 #define inf 0x7fffffff
 20 #define maxm 1001
 21 #define mod 998244353
 22 //#define LOCAL
 23 using namespace std;
 24 int read(){
 25     int x=0,f=1;char ch=getchar();
 26     while(ch<'0'||ch>'9'){if(ch=='-')f=-1;ch=getchar();}
 27     while(ch>='0'&&ch<='9'){x=x*10+ch-'0';ch=getchar();}
 28     return x*f;
 29 }
 30 int dp[220][55];
 31 int t_use[55];
 32 vector<int> go[220][55];
 33 int main() 
 34 {
 35     int n,T,icase=1,times;
 36     while ((cin>>n)&&n) {
 37         cin>>T;
 38         int m1,m2;
 39         for (int i=1;i<=n-1;++i) cin>>t_use[i];
 40         for (int i=0;i<=T;++i) 
 41             for (int j=1;j<=n;++j)
 42                 go[i][j].clear();
 43         cin>>m1;
 44         for (int i=1;i<=m1;++i) {
 45             cin>>times;
 46             int t=times;
 47             if(t>T) continue;
 48             go[t][1].push_back(i);
 49             for (int j=1;j<=n-1;++j) {
 50                 t+=t_use[j];
 51                 if (t>T) break;
 52                 go[t][j+1].push_back(i);
 53             }
 54         }
 55         cin>>m2;
 56         for (int i=1;i<=m2;++i) {
 57             cin>>times;
 58             int t=times;
 59             if (t>T) continue;
 60             go[t][n].push_back(i+m1);
 61             for (int j=n-1;j>=1;--j) {
 62                 t+=t_use[j];
 63                 if(t>T) break;
 64                 go[t][j].push_back(i+m1);
 65             }
 66         }
 67         for (int i=0;i<=T;++i)
 68             for (int j=1;j<=n;++j)
 69                 dp[i][j]=inf;
 70         dp[0][1]=0;
 71         for (int i=0;i<T;++i) {
 72             for (int j=1;j<=n;++j) {
 73                 if (dp[i][j]==inf) continue;
 74                 int size=go[i][j].size();
 75                 dp[i+1][j]=min(dp[i+1][j],dp[i][j]+1);
 76                 for (int k=0;k<size;++k) {
 77                     int u=go[i][j][k];
 78                     if (u<=m1&&j<n) {
 79                         if (i+t_use[j]<=T) {
 80                             dp[i+t_use[j]][j+1]=min(dp[i+t_use[j]][j+1],dp[i][j]);
 81                         }
 82                     }
 83                     else if (j>1&&u>m1) {
 84                         if (i+t_use[j-1]<=T) {
 85                             dp[i+t_use[j-1]][j-1]=min(dp[i+t_use[j-1]][j-1], dp[i][j]);
 86                         }
 87                     }
 88                 }
 89             }
 90         }
 91         int ans=inf;
 92         for (int i=0;i<=T;++i) {
 93             if (dp[i][n]==inf) continue;
 94             ans=min(ans,dp[i][n]+T-i);
 95         }
 96         if (ans==inf) {
 97             cout<<"Case Number "<<icase++<<": impossible"<<endl;
 98         }
 99         else {
100             cout<<"Case Number "<<icase++<<": "<<ans<<endl;
101         }
102     }
103     return 0;
104 }
105 /*
106 4
107 55
108 5 10 15
109 4
110 0 5 10 20
111 4
112 0 5 10 15
113 4
114 18
115 1 2 3
116 5
117 0 3 6 10 12
118 6
119 0 3 5 7 12 15
120 2
121 30
122 20
123 1
124 20
125 7
126 1 3 5 7 11 13 17
127 0
128 */
uva 1025

 

 

六自由度机械臂ANN人工神经网络设计:正向逆向运动学求解、正向动力学控制、拉格朗日-欧拉法推导逆向动力学方程(Matlab代码实现)内容概要:本文档围绕六自由度机械臂的ANN人工神经网络设计展开,详细介绍了正向与逆向运动学求解、正向动力学控制以及基于拉格朗日-欧拉法推导逆向动力学方程的理论与Matlab代码实现过程。文档还涵盖了PINN物理信息神经网络在微分方程求解、主动噪声控制、天线分析、电动汽车调度、储能优化等多个工程与科研领域的应用案例,并提供了丰富的Matlab/Simulink仿真资源和技术支持方向,体现了其在多学科交叉仿真与优化中的综合性价值。; 适合人群:具备一定Matlab编程基础,从事机器人控制、自动化、智能制造、电力系统或相关工程领域研究的科研人员、研究生及工程师。; 使用场景及目标:①掌握六自由度机械臂的运动学与动力学建模方法;②学习人工神经网络在复杂非线性系统控制中的应用;③借助Matlab实现动力学方程推导与仿真验证;④拓展至路径规划、优化调度、信号处理等相关课题的研究与复现。; 阅读建议:建议按目录顺序系统学习,重点关注机械臂建模与神经网络控制部分的代码实现,结合提供的网盘资源进行实践操作,并参考文中列举的优化算法与仿真方法拓展自身研究思路。
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