题目链接:http://acm.hdu.edu.cn/showproblem.php?pid=2602
Bone Collector
Time Limit: 2000/1000 MS (Java/Others) Memory Limit: 32768/32768 K (Java/Others)
Total Submission(s): 54132 Accepted Submission(s):
22670
Problem Description
Many years ago , in Teddy’s hometown there was a man
who was called “Bone Collector”. This man like to collect varies of bones , such
as dog’s , cow’s , also he went to the grave …
The bone collector had a big bag with a volume of V ,and along his trip of collecting there are a lot of bones , obviously , different bone has different value and different volume, now given the each bone’s value along his trip , can you calculate out the maximum of the total value the bone collector can get ?
The bone collector had a big bag with a volume of V ,and along his trip of collecting there are a lot of bones , obviously , different bone has different value and different volume, now given the each bone’s value along his trip , can you calculate out the maximum of the total value the bone collector can get ?
Input
The first line contain a integer T , the number of
cases.
Followed by T cases , each case three lines , the first line contain two integer N , V, (N <= 1000 , V <= 1000 )representing the number of bones and the volume of his bag. And the second line contain N integers representing the value of each bone. The third line contain N integers representing the volume of each bone.
Followed by T cases , each case three lines , the first line contain two integer N , V, (N <= 1000 , V <= 1000 )representing the number of bones and the volume of his bag. And the second line contain N integers representing the value of each bone. The third line contain N integers representing the volume of each bone.
Output
One integer per line representing the maximum of the
total value (this number will be less than 231).
Sample Input
1
5 10
1 2 3 4 5
5 4 3 2 1
Sample Output
14
01背包问题,这种背包特点是:每种物品仅有一件,可以选择放或不放。
用子问题定义状态:即dp[i][v]表示前i件物品恰放入一个容量为v的背包可以获得的最大价值。
则其状态转移方程便是:
dp[i][v]=max{dp[i-1][v],dp[i-1][v-cost[i]]+value[i]}
用子问题定义状态:即dp[i][v]表示前i件物品恰放入一个容量为v的背包可以获得的最大价值。
则其状态转移方程便是:
dp[i][v]=max{dp[i-1][v],dp[i-1][v-cost[i]]+value[i]}
1 #include<iostream> 2 using namespace std; 3 int dp[1000][1000]; 4 5 int max(int x,int y) 6 { 7 return x>y?x:y; 8 } 9 10 int main() 11 { 12 int t,n,v,i,j; 13 int va[1000],vo[1000]; 14 cin>>t; 15 while(t--) 16 { 17 cin>>n>>v; 18 for(i=1;i<=n;i++) 19 cin>>va[i]; 20 for(i=1;i<=n;i++) 21 cin>>vo[i]; 22 memset(dp,0,sizeof(dp));//初始化操作 23 for(i=1;i<=n;i++) 24 { 25 for(j=0;j<=v;j++) 26 { 27 if(vo[i]<=j)//表示第i个物品将放入大小为j的背包中 28 dp[i][j]=max(dp[i-1][j],dp[i-1][j-vo[i]]+va[i]);//第i个物品放入后,那么前i-1个物品可能会放入也可能因为剩余空间不够无法放入 29 else //第i个物品无法放入 30 dp[i][j]=dp[i-1][j]; 31 } 32 } 33 cout<<dp[n][v]<<endl; 34 } 35 return 0; 36 }
该题的第二种解法就是对背包的优化解法,当然只能对空间就行优化,时间是不能优化的。
先考虑上面讲的基本思路如何实现,肯定是有一个主循环i=1..N,每次算出来二维数组dp[i][0..V]的所有值。
那么,如果只用一个数组dp[0..V],能不能保证第i次循环结束后dp[v]中表示的就是我们定义的状态dp[i][v]呢?
dp[i][v]是由dp[i-1][v]和dp[i-1][v-c[i]]两个子问题递推而来,能否保证在推dp[i][v]时(也即在第i次主循环中推dp[v]时)能够得到dp[i-1][v]和dp[i-1][v-c[i]]的值呢?事实上,这要求在每次主循环中我们以v=V..0的顺序推dp[v],这样才能保证推dp[v]时dp[v-c[i]]保存的是状态dp[i-1][v-c[i]]的值。伪代码如下:
for i=1..N
for v=V..0
dp[v]=max{dp[v],dp[v-c[i]]+w[i]};
注意:这种解法只能由V--0,不能反过来,如果反过来就会造成物品重复放置!
1 #include<iostream> 2 using namespace std; 3 #define Size 1111 4 int va[Size],vo[Size]; 5 int dp[Size]; 6 int Max(int x,int y) 7 { 8 return x>y?x:y; 9 } 10 int main() 11 { 12 int t,n,v; 13 int i,j; 14 cin>>t; 15 while(t--) 16 { 17 cin>>n>>v; 18 for(i=1;i<=n;i++) 19 cin>>va[i]; 20 for(i=1;i<=n;i++) 21 cin>>vo[i]; 22 memset(dp,0,sizeof(dp)); 23 for(i=1;i<=n;i++) 24 { 25 for(j=v;j>=vo[i];j--) 26 { 27 dp[j]=Max(dp[j],dp[j-vo[i]]+va[i]); 28 } 29 } 30 cout<<dp[v]<<endl; 31 } 32 return 0; 33 }