邮票问题(动态规划)

该代码实现了一个解决邮票组合问题的算法,给定不同面额的邮票和每种面额邮票的数量,找出能组合成的最多连续面额数。输入包括邮票种类数m、每种邮票的数量n以及邮票面额,输出为最大连续面额数。通过动态规划的方法,遍历所有可能的面额组合,当组合面额超过设定的最大张数时停止计算并输出结果。

 题目意思:

设有已知面额的邮票m种,每种有n张,用总数不超过n张的邮票,能从面额1开始,最多连续组成多少面额。(1≤m≤100,1≤n≤100,1≤邮票面额≤255)

输入

第一行:m,n的值,中间用一空格隔开。

第二行:A[1..m](面额),每个数中间用一空格隔开。

输出

连续面额数的最大值

样例输入 Copy

3  4
1  2  4

样例输出 Copy

14

代码:

#include<stdio.h>
#include<iostream>
#include<algorithm>
using namespace std;
int a[105],s[30000];

int main()
{
	int n,m;
	cin>>n>>m;
	for(int i=1;i<=n;i++)
		cin>>a[i];
	sort(a+1,a+1+n);
	if(a[1]!=1)
		cout<<"0"<<endl;
	else
	{//肯定有1面额-->凑一只用一张,s[1]=1 
		s[1]=1;//所凑面额最小张数超出范围说明这时候能凑得数是最大的 
		for(int i=2;;i++)//找面额,s[]为所凑面额最小张数 
		{//每种不能超出n张,j<=n 
			for(int j=1;j<=n && a[j]<=i;j++)//选取面额要小于要凑的数 
			{//用a[j]这一张, 
				if(s[i]==0 || s[i]>s[i-a[j]]+1)//s[i]还没赋值或所用数大于 大于 
					 s[i]=s[i-a[j]]+1;
			}
			if(s[i]>m)
			{
				cout<<i-1<<endl;
				break;
			}
		}
	}
	return 0;
}

DESCRIPTION: 1.Analyze Problem A : sorted stamps array A={ai} ai: one stamp element in array n: array size, that is number of elements in array r: desired value of stamps F(n,r):expected result, minimum number of stamps for a given value r from n size array. S: selected stamps array S={si} 2.Choose Algorithm a.Greedy algorithm seems to be a good choice, try to solve it in O(n), i try divide array into subarry B={bi}, r should larger than every elemnt in B that is r>bi and suppose bk is the smallest element in B, so that r= bk%r, f(i,r)=(bk/r), F(n,r)=∑f(i,r). The main idea is to choose the last element who larger than desired value each time. However,it can not give us optimal solution in some condition, like A={8,5,4,1}, if r=10, this algoritm will give a solution F(n,r)=3, S={8,1,1},but the optimal solution should be F(n,r)=2, S={5,5}. b.Full search so the straight forwards algorithm is to search for every solution in A for desired value directly.However, it will always take O(n!) to go through every combination. c.Dynamic programming, at last, I decide to choose dynamic programming. analyze optimal structure, suppose in A={ai}, for a specific stamp ak,there will be two cases it is choosen so that f(i,r)=1+f(i,r-ak) , 1<=i<=k, r>=ak it is not valid so that f(i,r)=f(i-1,r) 3.Design Dynamic programming optimal structure: Compute-opt(r)= 1 + Compute-opt(r-ai) value: Compute-opt(r) = ∞ (r < 0) Compute-opt(r) = 0 (r = 0) Compute-opt(r) = 1+{Compute-opt(r-ai)} ( 1=<i<=n, r>ai>0 ) Complexity :O(nr) Memory cost:O(n+r) Compute in a bottom-up style to recursive every desired value and array. store value of Compute-opt in memory for future use, so that we can easily get value from those memory in future recursive call, and avoid compute again, that is if the array is not change, you can easily fetch result any desired value j (j < r, r is the value using for compute ). 2.For User totally, I design a small command line for this machine list below 1.Manual Operation 2.Self Auto Testing 3.Check Results q.Quit Manual Operation: when select this machine will turn to be manual mode, ask person to input stamps and desired value; Self Auto Testing:when select this machine will turn to be auto mode, show the test case already design in code after that machine will quit automatically. Check Results: only be visiable in Manual Operation, people can check desired value for the array input before, the desired value should be no more than first time input. Quit, clean all the memory and quit system.
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