joj1966

 1966: Super Market III


ResultTIME LimitMEMORY LimitRun TimesAC TimesJUDGE
1s 10240K 177 75 Standard

A supermarket has a set Prod of products on sale. It earns a profit px for each product x∈Prod sold by a deadline dx that is measured as an integral number of time units starting from the moment the sale begins. Each product takes precisely one unit of time for being sold. A selling schedule is an ordered subset of products Sell ≤ Prod such that the selling of each product x∈Sell, according to the ordering of Sell, completes before the deadline dx or just when dx expires. The profit of the selling schedule is Profit(Sell)=Σx∈Sellpx. An optimal selling schedule is a schedule with a maximum profit. 
For example, consider the products Prod={a,b,c,d} with (pa,da)=(50,2), (pb,db)=(10,1), (pc,dc)=(20,2), and (pd,dd)=(30,1). The possible selling schedules are listed in table 1. For instance, the schedule Sell={d,a} shows that the selling of product d starts at time 0 and ends at time 1, while the selling of product a starts at time 1 and ends at time 2. Each of these products is sold by its deadline. Sell is the optimal schedule and its profit is 80. 


Write a program that reads sets of products from an input text file and computes the profit of an optimal selling schedule for each set of products. 

Input

A set of products starts with an integer 0 <= n <= 10000, which is the number of products in the set, and continues with n pairs pi di of integers, 1 <= pi <= 10000 and 1 <= di <= 10000, that designate the profit and the selling deadline of the i-th product. White spaces can occur freely in input. Input data terminate with an end of file and are guaranteed correct.

Output

For each set of products, the program prints on the standard output the profit of an optimal selling schedule for the set. Each result is printed from the beginning of a separate line.

Sample Input

4  50 2  10 1   20 2   30 1

7  20 1   2 1   10 3  100 2   8 2
   5 20  50 10

Sample Output

80
185

这个问题是并查集的应用,本来做这个题目是为了检验书上的代码是不是正确的。结果按书上的思是错误的不知道是我理解错了还是书上的代码错了。只能自己按自己的思路想了一个方法。。不过我觉得老师说的最有权威的一句话就是“你的想法可能是正确的但是考试要按照我的的来!!!”
#include<stdio.h>
#include<iostream>
#include<algorithm>
#include<string.h>
using namespace std;
struct NODE
{
    int profile;
    int deadline;
};
int f[10001];
NODE node[10001];
bool cmp(const NODE &n1,const NODE&n2)
{
    return n1.profile>n2.profile;
}
int find(int u)
{
    return f[u]=(f[u]==u?u:find(f[u]));
}
int cal(int n)
{
    int k=0;
    for(int i=0;i<=n;i++)f[i]=i;
    for(int i=1;i<=n;i++)
    {
        int j=find(min(n,node[i].deadline));
        if(j!=0)
        {
            int u=find(j-1);
            k+=node[i].profile;
            f[j]=u;
        }
    }
    return k;
}
int main()
{
    //freopen("in.txt","r",stdin);
    int n;
    while(cin>>n)
    {
        for(int i=1;i<=n;i++)
        {
            scanf("%d%d",&node[i].profile,&node[i].deadline);
        }
        sort(node+1,node+n+1,cmp);
        cout<<cal(n)<<endl;
    }
    return 0;
}

【电动车】基于多目标优化遗传算法NSGAII的峰谷分时电价引导下的电动汽车充电负荷优化研究(Matlab代码实现)内容概要:本文围绕“基于多目标优化遗传算法NSGA-II的峰谷分时电价引导下的电动汽车充电负荷优化研究”展开,利用Matlab代码实现优化模型,旨在通过峰谷分时电价机制引导电动汽车有序充电,降低电网负荷波动,提升能源利用效率。研究融合了多目标优化思想与遗传算法NSGA-II,兼顾电网负荷均衡性、用户充电成本和充电满意度等多个目标,构建了科学合理的数学模型,并通过仿真验证了方法的有效性与实用性。文中还提供了完整的Matlab代码实现路径,便于复现与进一步研究。; 适合人群:具备一定电力系统基础知识和Matlab编程能力的高校研究生、科研人员及从事智能电网、电动汽车调度相关工作的工程技术人员。; 使用场景及目标:①应用于智能电网中电动汽车充电负荷的优化调度;②服务于峰谷电价政策下的需求侧管理研究;③为多目标优化算法在能源系统中的实际应用提供案例参考; 阅读建议:建议读者结合Matlab代码逐步理解模型构建与算法实现过程,重点关注NSGA-II算法在多目标优化中的适应度函数设计、约束处理及Pareto前沿生成机制,同时可尝试调整参数或引入其他智能算法进行对比分析,以深化对优化策略的理解。
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