hdu 5432 Pyramid Split【二分查找】

本文深入探讨了一种独特的数学挑战——通过精确的几何操作将多个金字塔分割成两部分,使得每一部分的体积相等。利用剑‘TuLong’进行平面切割,作者揭示了解决该问题的关键步骤和算法,包括输入解析、体积计算以及找到平均切割平面的高度。通过实例分析和代码实现,展示了如何在有限的时间内高效地解决这一问题。

Pyramid Split

Time Limit: 4000/2000 MS (Java/Others)    Memory Limit: 65536/65536 K (Java/Others)
Total Submission(s): 880    Accepted Submission(s): 352


Problem Description
Xiao Ming is a citizen who's good at playing,he has lot's of gold cones which have square undersides,let's call them pyramids.

Anyone of them can be defined by the square's length and the height,called them width and height.

To easily understand,all the units are mile.Now Ming has n pyramids,there height and width are known,Xiao Ming wants to make them again to get two objects with the same volume.

Of course he won't simply melt his pyramids and distribute to two parts.He has a sword named "Tu Long" which can cut anything easily.

Now he put all pyramids on the ground (the usdersides close the ground)and cut a plane which is parallel with the water level by his sword ,call this plane cutting plane.

Our mission is to find a cutting plane that makes the sum of volume above the plane same as the below,and this plane is average cutting plane.Figure out the height of average cutting plane.
 


Input
First line: T, the number of testcases.(1T100)

Then T testcases follow.In each testcase print three lines :

The first line contains one integers n(1n10000), the number of operations.

The second line contains n integers A1,,An(1in,1Ai1000) represent the height of the ith pyramid.



The third line contains n integers B1,,Bn(1in,1Bi100) represent the width of the ith pyramid.
 


Output
For each testcase print a integer - **the height of average cutting plane**.

(the results take the integer part,like 15.8 you should output 15)
 


Sample Input
2 2 6 5 10 7 8 702 983 144 268 732 166 247 569 20 37 51 61 39 5 79 99
 


Sample Output
1 98


这个题AC的我好伤心、我的思路是每一个正四棱锥都找到那个高度,然后加在一起除n得到结果,但是最终还是因为精度问题。无限的wa、

最后找到各路大牛的思路,从整体找到这个高度,就能AC了:

#include<stdio.h>
#include<string.h>
#include<iostream>
#include<math.h>
#define EPS 1e-5
using namespace std;
double x[11000];
double h[11000];
int main()
{
    int t;
    scanf("%d",&t);
    while(t--)
    {
        int n;
        double r=0;
        scanf("%d",&n);
        for(int i=0;i<n;i++)
        {
            scanf("%lf",h+i);
            r=max(r,h[i]);
        }
        double v=0;//这里在写的时候,忘记=0,奇葩的是编译器竟然没有爆数据、、然后一直在wa啊wa
        for(int j=0;j<n;j++)
        {
            scanf("%lf",&x[j]);
            v+=x[j]*x[j]*h[j]/3;
        }
        double l=0;
        double mid;
        while(r-l>EPS)
        {
            mid=(l+r)/2;
            double vv=0;
            for(int j=0;j<n;j++)
            {
                if(h[j]>mid)
                vv+=(h[j]-mid)*(h[j]-mid)*(h[j]-mid)*x[j]*x[j]/h[j]/h[j]/3;
            }
            if(vv*2>v)
            l=mid;
            else
            r=mid;
        }
        printf("%d\n",(int)(l+EPS));
    }
    return 0;
}






【电动汽车充电站有序充电调度的分散式优化】基于蒙特卡诺和拉格朗日的电动汽车优化调度(分时电价调度)(Matlab代码实现)内容概要:本文介绍了基于蒙特卡洛和拉格朗日方法的电动汽车充电站有序充电调度优化方案,重点在于采用分散式优化策略应对分时电价机制下的充电需求管理。通过构建数学模型,结合不确定性因素如用户充电行为和电网负荷波动,利用蒙特卡洛模拟生成大量场景,并运用拉格朗日松弛法对复杂问题进行分解求解,从而实现全局最优或近似最优的充电调度计划。该方法有效降低了电网峰值负荷压力,提升了充电站运营效率与经济效益,同时兼顾用户充电便利性。 适合人群:具备一定电力系统、优化算法和Matlab编程基础的高校研究生、科研人员及从事智能电网、电动汽车相关领域的工程技术人员。 使用场景及目标:①应用于电动汽车充电站的日常运营管理,优化充电负荷分布;②服务于城市智能交通系统规划,提升电网与交通系统的协同水平;③作为学术研究案例,用于验证分散式优化算法在复杂能源系统中的有效性。 阅读建议:建议读者结合Matlab代码实现部分,深入理解蒙特卡洛模拟与拉格朗日松弛法的具体实施步骤,重点关注场景生成、约束处理与迭代收敛过程,以便在实际项目中灵活应用与改进。
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