POJ2184 Cow Exhibition 变种01背包

本文介绍了一种基于背包问题的算法,用于从一群牛中选择最优组合,使得牛群的总智能与乐趣值最大且非负。通过调整数组存储方式,算法有效处理了数值可能为负的情况。

摘要生成于 C知道 ,由 DeepSeek-R1 满血版支持, 前往体验 >

               

Description

"Fat and docile, big and dumb, they look so stupid, they aren't much
fun..."
- Cows with Guns by Dana Lyons

The cows want to prove to the public that they are both smart and fun. In order to do this, Bessie has organized an exhibition that will be put on by the cows. She has given each of the N (1 <= N <= 100) cows a thorough interview and determined two values for each cow: the smartness Si (-1000 <= Si <= 1000) of the cow and the funness Fi (-1000 <= Fi <= 1000) of the cow.

Bessie must choose which cows she wants to bring to her exhibition. She believes that the total smartness TS of the group is the sum of the Si's and, likewise, the total funness TF of the group is the sum of the Fi's. Bessie wants to maximize the sum of TS and TF, but she also wants both of these values to be non-negative (since she must also show that the cows are well-rounded; a negative TS or TF would ruin this). Help Bessie maximize the sum of TS and TF without letting either of these values become negative.

Input

* Line 1: A single integer N, the number of cows

* Lines 2..N+1: Two space-separated integers Si and Fi, respectively the smartness and funness for each cow.

Output

* Line 1: One integer: the optimal sum of TS and TF such that both TS and TF are non-negative. If no subset of the cows has non-negative TS and non- negative TF, print 0.

Sample Input

5-5 78 -66 -32 1-8 -5

Sample Output

8

Hint

OUTPUT DETAILS:

Bessie chooses cows 1, 3, and 4, giving values of TS = -5+6+2 = 3 and TF
= 7-3+1 = 5, so 3+5 = 8. Note that adding cow 2 would improve the value
of TS+TF to 10, but the new value of TF would be negative, so it is not
allowed.
 
题意:每行给出si和fi,代表牛的两个属性,然后要求选出几头牛,是的则求出总S与总F的和,注意S与F都不能为负数
思路:很明显的就是取与不取的问题,对于这类问题的第一想法就是背包,但是这道题目很明显与一般的背包不同,因为有负数,但是联想到以前也有这种将负数存入下标的情况,那就是将数组开大,换一种存法
我们用dp[i]存放每个s[i]能得到的最佳F,那么我们就可以根据s[i]的取值采取两种不同的01背包取法,在取完之后,然后再根据背包的有无再去求得最佳答案即可
 
#include <stdio.h>#include <string.h>#include <algorithm>using namespace std;int dp[200005];const int inf = 1<<30;int main(){    int n,s[200],f[200],i,j,ans;    while(~scanf("%d",&n))    {        for(i = 0; i<=200000; i++)            dp[i] = -inf;        dp[100000] = 0;        for(i = 1; i<=n; i++)            scanf("%d%d",&s[i],&f[i]);        for(i = 1; i<=n; i++)        {            if(s[i]<0 && f[i]<0)                continue;            if(s[i]>0)            {                for(j = 200000; j>=s[i]; j--)//如果s[i]为整数,那么我们就从大的往小的方向进行背包                    if(dp[j-s[i]]>-inf)                        dp[j] = max(dp[j],dp[j-s[i]]+f[i]);            }            else            {                for(j = s[i]; j<=200000+s[i]; j++)//为负数则需要反过来                    if(dp[j-s[i]]>-inf)                        dp[j] = max(dp[j],dp[j-s[i]]+f[i]);            }        }        ans = -inf;        for(i = 100000; i<=200000; i++)//因为区间100000~200000才是表示的整数,那么此时的i就是之前背包中的s[i],如果此时dp[i]也就是f[i]大于等于0的话,我们再加上s[i](此时为i),然后减去作为界限的100000,就可以得到答案        {            if(dp[i]>=0)                ans = max(ans,dp[i]+i-100000);        }        printf("%d\n",ans);    }    return 0;}

           
内容概要:本文档详细介绍了基于MATLAB实现多目标差分进化(MODE)算法进行无人机三维路径规划的项目实例。项目旨在提升无人机在复杂三维环境中路径规划的精度、实时性、多目标协调处理能力、障碍物避让能力和路径平滑性。通过引入多目标差分进化算法,项目解决了传统路径规划算法在动态环境和多目标优化中的不足,实现了路径长度、飞行安全距离、能耗等多个目标的协调优化。文档涵盖了环境建模、路径编码、多目标优化策略、障碍物检测与避让、路径平滑处理等关键技术模块,并提供了部分MATLAB代码示例。 适合人群:具备一定编程基础,对无人机路径规划和多目标优化算法感兴趣的科研人员、工程师和研究生。 使用场景及目标:①适用于无人机在军事侦察、环境监测、灾害救援、物流运输、城市管理等领域的三维路径规划;②通过多目标差分进化算法,优化路径长度、飞行安全距离、能耗等多目标,提升无人机任务执行效率和安全性;③解决动态环境变化、实时路径调整和复杂障碍物避让等问题。 其他说明:项目采用模块化设计,便于集成不同的优化目标和动态环境因素,支持后续算法升级与功能扩展。通过系统实现和仿真实验验证,项目不仅提升了理论研究的实用价值,还为无人机智能自主飞行提供了技术基础。文档提供了详细的代码示例,有助于读者深入理解和实践该项目。
评论
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值