Battle Ships is a new game which is similar to Star Craft. In this game, the enemy builds a defense tower, which has L longevity. The player has a military factory, which can produce N kinds of battle ships. The factory takes ti seconds to produce the i-th battle ship and this battle ship can make the tower loss li longevity every second when it has been produced. If the longevity of the tower lower than or equal to 0, the player wins. Notice that at each time, the factory can choose only one kind of battle ships to produce or do nothing. And producing more than one battle ships of the same kind is acceptable.
Your job is to find out the minimum time the player should spend to win the game.
Input
There are multiple test cases.
The first line of each case contains two integers N(1 ≤ N ≤ 30) and L(1 ≤ L ≤ 330), N is the number of the kinds of Battle Ships, L is the longevity of the Defense Tower. Then the following N lines, each line contains two integers t i(1 ≤ t i ≤ 20) and li(1 ≤ li ≤ 330) indicating the produce time and the lethality of the i-th kind Battle Ships.
Output
Output one line for each test case. An integer indicating the minimum time the player should spend to win the game.
Sample Input
1 1 1 1 2 10 1 1 2 5 3 100 1 10 3 20 10 100
Sample Output
2 4 5
Author: FU, Yujun
Contest: ZOJ Monthly, July 2012
//dp[i]代表时间为i时最多可以打掉的血
//然后找到第一个dp[i]>=L,那么就是最短的时间
//采用的是用当前状态去更新后面状态
//对于,j+T[i]时间段内,
//dp[j]更新dp[j+T[i]],表示一开始的T[i]秒是在建武器i
//在j的时间段内武器i一直都在工作,然后J时间段内套用j+T[i]时间段内的含义.
//所以该动规方法是可行的
#include <iostream> #include <stdio.h> #include <string.h> #include <algorithm> using namespace std; int N,L; int T[34],l[34]; int dp[334]; int main() { int i,j; while(scanf("%d%d",&N,&L)!=EOF) { for(i=1;i<=N;i++) scanf("%d%d",&T[i],&l[i]); memset(dp,0,sizeof(dp)); for(j=1;j<=L;j++) for(i=1;i<=N;i++) dp[j+T[i]]=max(dp[j]+l[i]*j,dp[j+T[i]]); for(i=1;i<=330;i++) if(dp[i]>=L) break; printf("%d\n",i); } return 0; }
本文探讨了一款类似于《星际争霸》的游戏《战斗舰船》,玩家需在限定时间内通过军事工厂生产不同类型的战斗舰船,攻击敌方防御塔。文章详细介绍了如何利用动态规划算法在给定时间限制下最大化击败防御塔的血量,以求赢得游戏。通过实例分析和代码实现,展示了如何优化生产策略以最小化获胜所需时间。
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