HDOJ -- 1260 Tickets

Tickets
Time Limit:1000MS     Memory Limit:32768KB     64bit IO Format:%I64d & %I64u

Description

Jesus, what a great movie! Thousands of people are rushing to the cinema. However, this is really a tuff time for Joe who sells the film tickets. He is wandering when could he go back home as early as possible. 
A good approach, reducing the total time of tickets selling, is let adjacent people buy tickets together. As the restriction of the Ticket Seller Machine, Joe can sell a single ticket or two adjacent tickets at a time. 
Since you are the great JESUS, you know exactly how much time needed for every person to buy a single ticket or two tickets for him/her. Could you so kind to tell poor Joe at what time could he go back home as early as possible? If so, I guess Joe would full of appreciation for your help. 

Input

There are N(1<=N<=10) different scenarios, each scenario consists of 3 lines: 
1) An integer K(1<=K<=2000) representing the total number of people; 
2) K integer numbers(0s<=Si<=25s) representing the time consumed to buy a ticket for each person; 
3) (K-1) integer numbers(0s<=Di<=50s) representing the time needed for two adjacent people to buy two tickets together. 

Output

For every scenario, please tell Joe at what time could he go back home as early as possible. Every day Joe started his work at 08:00:00 am. The format of time is HH:MM:SS am|pm. 

Sample Input

2
2
20 25
40
1
8

Sample Output

08:00:40 am
08:00:08 am

题目大意:总共有N个人,给出每个人单独买票的时间,以及相邻两人一起买票的时间,求出N个人买完票后所用时间的最小值。
简单DP,注意下输出格式就行了。用数组one[i]表示第i个人单独买票所用的时间;用数组two[i]表示第i个人和第i-1个人一起买票所用的时间;再用数组dp[i]记录前i个人买完票后所用的最少时间。那么就可以写出其状态转移方程:dp[i]=min(dp[i-1]+one[i],dp[i-2],two[i])。代码如下:
#include<cstdio>
#include<cstring>
#include<algorithm>
using namespace std;
int main(){
	int dp[10005];
	int one[60005],two[60005];
	int N,k;
	int h,m,s;
	char a[5]={'a','m'};
	scanf("%d",&N);
	while(N--){
		scanf("%d",&k);
		for(int i=1;i<=k;i++)
			scanf("%d",&one[i]);
		for(int i=2;i<=k;i++)//i从2开始!! 
			scanf("%d",&two[i]);
		memset(dp,0,sizeof(dp));
		dp[1]=one[1];
		for(int i=2;i<=k;i++)
			dp[i]=min(dp[i-1]+one[i],dp[i-2]+two[i]);
		h=8+dp[k]/3600;//时 
		m=dp[k]%3600/60;//分 
		s=(dp[k]%3600)%60;//秒 
		if(h>=12){
			if(h>12)
				h-=12;
			a[0]='p';
		}
		printf("%02d:%02d:%02d %s\n",h,m,s,a);
	}
	return 0;
}

多源动态最优潮流的分布鲁棒优化方法(IEEE118节点)(Matlab代码实现)内容概要:本文介绍了基于Matlab代码实现的多源动态最优潮流的分布鲁棒优化方法,适用于IEEE118节点电力系统。该方法结合两阶段鲁棒模型与确定性模型,旨在应对电力系统中多源输入(如可再生能源)的不确定性,提升系统运行的安全性与经济性。文中详细阐述了分布鲁棒优化的建模思路,包括不确定性集合的构建、目标函数的设计以及约束条件的处理,并通过Matlab编程实现算法求解,提供了完整的仿真流程与结果分析。此外,文档还列举了大量相关电力系统优化研究案例,涵盖微电网调度、电动汽车集群并网、需求响应、储能配置等多个方向,展示了其在实际工程中的广泛应用价值。; 适合人群:具备一定电力系统基础知识和Matlab编程能力的研究生、科研人员及从事能源系统优化工作的工程师。; 使用场景及目标:①用于研究高比例可再生能源接入背景下电力系统的动态最优潮流问题;②支撑科研工作中对分布鲁棒优化模型的复现与改进;③为电力系统调度、规划及运行决策提供理论支持与仿真工具。; 阅读建议:建议读者结合提供的Matlab代码与IEEE118节点系统参数进行实操演练,深入理解分布鲁棒优化的建模逻辑与求解过程,同时可参考文中提及的其他优化案例拓展研究思路。
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