poj3169----查分约束系统的应用

本文探讨了一种布局问题,即如何安排一群有特定距离偏好的牛的位置,以满足它们之间的最大和最小距离限制。通过将问题转化为图的最短路径问题,利用差分约束系统进行求解,并给出了具体的实现代码。

Layout
Time Limit: 1000MS Memory Limit: 65536K
Total Submissions: 11702 Accepted: 5603
Description

Like everyone else, cows like to stand close to their friends when queuing for feed. FJ has N (2 <= N <= 1,000) cows numbered 1..N standing along a straight line waiting for feed. The cows are standing in the same order as they are numbered, and since they can be rather pushy, it is possible that two or more cows can line up at exactly the same location (that is, if we think of each cow as being located at some coordinate on a number line, then it is possible for two or more cows to share the same coordinate).

Some cows like each other and want to be within a certain distance of each other in line. Some really dislike each other and want to be separated by at least a certain distance. A list of ML (1 <= ML <= 10,000) constraints describes which cows like each other and the maximum distance by which they may be separated; a subsequent list of MD constraints (1 <= MD <= 10,000) tells which cows dislike each other and the minimum distance by which they must be separated.

Your job is to compute, if possible, the maximum possible distance between cow 1 and cow N that satisfies the distance constraints.
Input

Line 1: Three space-separated integers: N, ML, and MD.

Lines 2..ML+1: Each line contains three space-separated positive integers: A, B, and D, with 1 <= A < B <= N. Cows A and B must be at most D (1 <= D <= 1,000,000) apart.

Lines ML+2..ML+MD+1: Each line contains three space-separated positive integers: A, B, and D, with 1 <= A < B <= N. Cows A and B must be at least D (1 <= D <= 1,000,000) apart.
Output

Line 1: A single integer. If no line-up is possible, output -1. If cows 1 and N can be arbitrarily far apart, output -2. Otherwise output the greatest possible distance between cows 1 and N.
Sample Input

4 2 1
1 3 10
2 4 20
2 3 3
Sample Output

27
Hint

Explanation of the sample:

There are 4 cows. Cows #1 and #3 must be no more than 10 units apart, cows #2 and #4 must be no more than 20 units apart, and cows #2 and #3 dislike each other and must be no fewer than 3 units apart.

The best layout, in terms of coordinates on a number line, is to put cow #1 at 0, cow #2 at 7, cow #3 at 10, and cow #4 at 27.

解题思路:这里使用查分约束系统,将一个线性规划的问题转换成图的最短路径问题,查分约束系统详情可查看http://blog.youkuaiyun.com/xuezhongfenfei/article/details/8685313

#include <iostream>
#include <memory>
#include <limits.h>
#include <algorithm>
using namespace std;
const int MAX_N = 1000;
const int MAX_ML = 10000;
const int MAX_MD = 10000;
int d[MAX_N];

int AL[MAX_ML];
int BL[MAX_ML];
int DL[MAX_ML];

int AD[MAX_MD];
int BD[MAX_MD];
int DD[MAX_MD];
int main() {
    int N,ML,MD;
    cin>>N>>ML>>MD;
    fill(d,d + N,INT_MAX);
    for(int i = 0;i < ML;i++){
        cin>>AL[i]>>BL[i]>>DL[i];
    }
    for(int i = 0;i < MD;i++){
        cin>>AD[i]>>BD[i]>>DD[i];
    }
    d[0] = 0;
    //使用Bellman_Ford求解
    for(int k = 0;k < N - 1;k++){
        for(int i = 0;i + 1 < N;i++){
            //d[i]<=d[i+!],从i+1向i引一条权值为0的边
            if(d[i + 1] < INT_MAX){
                d[i] = min(d[i],d[i + 1]);
            }
        }
        for(int i = 0;i < ML;i++){
            //d[AL[i] - 1] + DL[i]>=d[BL[i] - 1],从AL[i] - 1向BL[i] - 1引一条权值为DL[i]的边
            if(d[AL[i] - 1] < INT_MAX){
                d[BL[i] - 1] = min(d[BL[i] - 1],d[AL[i] - 1] + DL[i]);
            }
        }
        for(int i = 0;i < MD;i++){
            //d[AD[i] - 1] + DL[i]<=d[BD[i] - 1],从BD[i] - 1向AD[i] - 1引一条权值为-DD[i]的边
            if(d[BD[i] - 1] < INT_MAX){
                d[AD[i] - 1] = min(d[AD[i] - 1],d[BD[i] - 1] - DD[i]);
            }
        }
    }
    int res = d[N - 1];
    //检测是否有负环
    for(int i = 0;i + 1 < N;i++){
        if(d[i + 1] < INT_MAX && d[i] > d[i + 1]){
            res = -1;
        }
    }
    for(int i = 0;i < ML;i++){
        if(d[AL[i] - 1] < INT_MAX && d[BL[i] - 1] > d[AL[i] - 1] + DL[i]){
            res = -1;
        }
    }
    for(int i = 0;i < MD;i++){
        if(d[BD[i] - 1] < INT_MAX && d[AD[i] - 1] > d[BD[i] - 1] - DD[i]){
            res = -1;
        }
    }

    if(res == INT_MAX){
        //解为无穷大
        res = -2;
    }
    cout<<res<<endl;
    return 0;
}
内容概要:本文系统介绍了算术优化算法(AOA)的基本原理、核心思想及Python实现方法,并通过图像分割的实际案例展示了其应用价值。AOA是一种基于种群的元启发式算法,其核心思想来源于四则运算,利用乘除运算进行全局勘探,加减运算进行局部开发,通过数学优化器加速函数(MOA)和数学优化概率(MOP)动态控制搜索过程,在全局探索与局部开发之间实现平衡。文章详细解析了算法的初始化、勘探与开发阶段的更新策略,并提供了完整的Python代码实现,结合Rastrigin函数进行测试验证。进一步地,以Flask框架搭建前后端分离系统,将AOA应用于图像分割任务,展示了其在实际工程中的可行性与高效性。最后,通过收敛速度、寻优精度等指标评估算法性能,并提出自适应参数调整、模型优化和并行计算等改进策略。; 适合人群:具备一定Python编程基础和优化算法基础知识的高校学生、科研人员及工程技术人员,尤其适合从事人工智能、图像处理、智能优化等领域的从业者;; 使用场景及目标:①理解元启发式算法的设计思想与实现机制;②掌握AOA在函数优化、图像分割等实际问题中的建模与求解方法;③学习如何将优化算法集成到Web系统中实现工程化应用;④为算法性能评估与改进提供实践参考; 阅读建议:建议读者结合代码逐行调试,深入理解算法流程中MOA与MOP的作用机制,尝试在不同测试函数上运行算法以观察性能差异,并可进一步扩展图像分割模块,引入更复杂的预处理或后处理技术以提升分割效果。
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