Codeforces 439D Devu and his Brother

题意:

给你n个数a[i]和m个数b[i],你每次能选择一个数组中的一个数加1或减1,问你最少需要操作几次才能使a数组的最小值大于等于b数组的最大值。

思路:

我们来考虑下最终的状态,最后数组a和数组b肯定是有一排一样的数,我们称这个数为中间值c,现在如何找到这个数呢?其实不需要找,我们来推导下:

假设有a为a数组中最小的数,b为b数组中最大的数,c为我们所要转换的中间值,设a加上x达到c,b减去y达到c。则有a+x=c,b-y=c将两式子相减有b-a=x+y。其实x+y就是我们所需要的操作数,所以思路就是将a数组从小到大排序下,b数组从大到小排序下,然后对于每个b大于a的数去算b-a(每个数只转换一次,最终变成什么数我们不关心,反正能变成他们之间的任意数)。

#include<cstdio>
#include<algorithm>
using namespace std;
typedef __int64 LL;

const int MAX=1e5+5;
int n,m;
LL a[MAX],b[MAX];

bool cmp(int a,int b){
	return a>b;
}

int main(){
	scanf("%d%d",&n,&m);
	for(int i=0;i<n;i++){
		scanf("%I64d",&a[i]);
	}
	for(int i=0;i<m;i++){
		scanf("%I64d",&b[i]);
	}
	sort(a,a+n);
	sort(b,b+m,cmp);
	LL ans=0;
	for(int i=0;i<min(n,m);i++){
		if(b[i]>a[i]) ans+=b[i]-a[i];
	}
	printf("%I64d\n",ans);
	return 0;
}


### Codeforces 1487D Problem Solution The problem described involves determining the maximum amount of a product that can be created from given quantities of ingredients under an idealized production process. For this specific case on Codeforces with problem number 1487D, while direct details about this exact question are not provided here, similar problems often involve resource allocation or limiting reagent type calculations. For instance, when faced with such constraints-based questions where multiple resources contribute to producing one unit of output but at different ratios, finding the bottleneck becomes crucial. In another context related to crafting items using various materials, it was determined that the formula `min(a[0],a[1],a[2]/2,a[3]/7,a[4]/4)` could represent how these limits interact[^1]. However, applying this directly without knowing specifics like what each array element represents in relation to the actual requirements for creating "philosophical stones" as mentioned would require adjustments based upon the precise conditions outlined within 1487D itself. To solve or discuss solutions effectively regarding Codeforces' challenge numbered 1487D: - Carefully read through all aspects presented by the contest organizers. - Identify which ingredient or component acts as the primary constraint towards achieving full capacity utilization. - Implement logic reflecting those relationships accurately; typically involving loops, conditionals, and possibly dynamic programming depending on complexity level required beyond simple minimum value determination across adjusted inputs. ```cpp #include <iostream> #include <vector> using namespace std; int main() { int n; cin >> n; vector<long long> a(n); for(int i=0;i<n;++i){ cin>>a[i]; } // Assuming indices correspond appropriately per problem statement's ratio requirement cout << min({a[0], a[1], a[2]/2LL, a[3]/7LL, a[4]/4LL}) << endl; } ``` --related questions-- 1. How does identifying bottlenecks help optimize algorithms solving constrained optimization problems? 2. What strategies should contestants adopt when translating mathematical formulas into code during competitive coding events? 3. Can you explain why understanding input-output relations is critical before implementing any algorithmic approach? 4. In what ways do prefix-suffix-middle frameworks enhance model training efficiency outside of just tokenization improvements? 5. Why might adjusting sample proportions specifically benefit models designed for tasks requiring both strong linguistic comprehension alongside logical reasoning skills?
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