P2979 [USACO10JAN]奶酪塔

题目描述

原题题面

FJ要建一个奶酪塔,高度最大为T。他有N种奶酪。第i种奶酪的高度为Hi(一定是5的倍数),价值为Vi。一块高度Hi>=K的奶酪被称为大奶酪,一个奶酪如果在它上方有大奶酪(如果有多块就只算一次),它的高度Hi就会变成原来的4/5.。FJ想让他的奶酪塔价值和最大。请你求出这个最大值。

输入格式:

第一行三个数N,T,K,意义如上所述。 接下来n行,每行两个数V_i,h_i(注意顺序)

输出格式:

奶酪塔的最大价值

输入输出样例

输入 #1

3 53 25 
100 25 
20 5 
40 10 

输出 #1

240 

【解题思路】:

(1)用数组f记录体积未被压缩时的最大价值

(2)用数组ff记录体积被压缩后的最大价值

(3)for循环枚举去掉最上面奶酪体积的最大价值ff[j]加上最上面的奶酪价值v[i]

(4)比较压缩前后的最大价值(如果不存在大奶酪,则ff数组均为0,输出压缩前最大价值;反之,压缩后最大价值必然大于等于压缩前最大价值)

【AC代码】:

#include <bits/stdc++.h>
#define M(a, b) memset(a, b, sizeof(a))
#define INF 0x3f3f3f3f
#define MOD 10000007
using namespace std;

inline void read(int &x){
    char ch=getchar(),c=ch;
	x=0;
    while(ch<'0' || ch>'9'){
    	 c=ch;
		 ch=getchar();
	}
    while(ch>='0' && ch<='9'){
    	x=(x<<1)+(x<<3)+ch-'0';
		ch=getchar();
	}
    if(c=='-')x=-x;
}

int n,T,k,ans,i,j;
int f[2000],v[1000],h[1000];

int main(){
    read(n),read(T),read(k);
    for(i=1;i<=n;i++) {
        read(v[i]),read(h[i]);
        for(j=h[i];j<=T*5/4;j++)f[j]=max(f[j],f[j-h[i]]+v[i]);
    }
    ans=f[T];
    for(i=1;i<=n;i++)
    	if(h[i]>=k)ans=max(ans,f[(T-h[i])*5/4]+v[i]);
    printf("%d\n",ans);
    return 0;
}
### USACO 2016 January Contest Subsequences Summing to Sevens Problem Solution and Explanation In this problem from the USACO contest, one is tasked with finding the size of the largest contiguous subsequence where the sum of elements (IDs) within that subsequence is divisible by seven. The input consists of an array representing cow IDs, and the goal is to determine how many cows are part of the longest sequence meeting these criteria; if no valid sequences exist, zero should be returned. To solve this challenge efficiently without checking all possible subsequences explicitly—which would lead to poor performance—a more sophisticated approach using prefix sums modulo 7 can be applied[^1]. By maintaining a record of seen remainders when dividing cumulative totals up until each point in the list by 7 along with their earliest occurrence index, it becomes feasible to identify qualifying segments quickly whenever another instance of any remainder reappears later on during iteration through the dataset[^2]. For implementation purposes: - Initialize variables `max_length` set initially at 0 for tracking maximum length found so far. - Use dictionary or similar structure named `remainder_positions`, starting off only knowing position `-1` maps to remainder `0`. - Iterate over given numbers while updating current_sum % 7 as you go. - Check whether updated value already exists inside your tracker (`remainder_positions`). If yes, compare distance between now versus stored location against max_length variable's content—update accordingly if greater than previous best result noted down previously. - Finally add entry into mapping table linking latest encountered modulus outcome back towards its corresponding spot within enumeration process just completed successfully after loop ends normally. Below shows Python code implementing described logic effectively handling edge cases gracefully too: ```python def find_largest_subsequence_divisible_by_seven(cow_ids): max_length = 0 remainder_positions = {0: -1} current_sum = 0 for i, id_value in enumerate(cow_ids): current_sum += id_value mod_result = current_sum % 7 if mod_result not in remainder_positions: remainder_positions[mod_result] = i else: start_index = remainder_positions[mod_result] segment_size = i - start_index if segment_size > max_length: max_length = segment_size return max_length ```
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