Booksort POJ - 3460 (IDA*)

本文介绍了一种图书馆中使用的图书排序算法,旨在通过最少的操作步骤将错位的书籍按唯一标识码升序排列。该算法采用迭代加深的A*搜索策略,并定义了一个评估函数来减少不必要的操作。

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The Leiden University Library has millions of books. When a student wants to borrow a certain book, he usually submits an online loan form. If the book is available, then the next day the student can go and get it at the loan counter. This is the modern way of borrowing books at the library.

There is one department in the library, full of bookcases, where still the old way of borrowing is in use. Students can simply walk around there, pick out the books they like and, after registration, take them home for at most three weeks.

Quite often, however, it happens that a student takes a book from the shelf, takes a closer look at it, decides that he does not want to read it, and puts it back. Unfortunately, not all students are very careful with this last step. Although each book has a unique identification code, by which the books are sorted in the bookcase, some students put back the books they have considered at the wrong place. They do put it back onto the right shelf. However, not at the right position on the shelf.

Other students use the unique identification code (which they can find in an online catalogue) to find the books they want to borrow. For them, it is important that the books are really sorted on this code. Also for the librarian, it is important that the books are sorted. It makes it much easier to check if perhaps some books are stolen: not borrowed, but yet missing.

Therefore, every week, the librarian makes a round through the department and sorts the books on every shelf. Sorting one shelf is doable, but still quite some work. The librarian has considered several algorithms for it, and decided that the easiest way for him to sort the books on a shelf, is by sorting by transpositions: as long as the books are not sorted,

take out a block of books (a number of books standing next to each other),
shift another block of books from the left or the right of the resulting ‘hole’, into this hole,
and put back the first block of books into the hole left open by the second block.
One such sequence of steps is called a transposition.

The following picture may clarify the steps of the algorithm, where X denotes the first block of books, and Y denotes the second block.

Original situation:
After step 1:
After step 2:
After step 3:
Of course, the librarian wants to minimize the work he has to do. That is, for every bookshelf, he wants to minimize the number of transpositions he must carry out to sort the books. In particular, he wants to know if the books on the shelf can be sorted by at most 4 transpositions. Can you tell him?

Input
The first line of the input file contains a single number: the number of test cases to follow. Each test case has the following format:

One line with one integer n with 1 ≤ n ≤ 15: the number of books on a certain shelf.
One line with the n integers 1, 2, …, n in some order, separated by single spaces: the unique identification codes of the n books in their current order on the shelf.
Output
For every test case in the input file, the output should contain a single line, containing:

if the minimal number of transpositions to sort the books on their unique identification codes (in increasing order) is T ≤ 4, then this minimal number T;
if at least 5 transpositions are needed to sort the books, then the message “5 or more”.
Sample Input
3
6
1 3 4 6 2 5
5
5 4 3 2 1
10
6 8 5 3 4 7 2 9 1 10
Sample Output
2
3
5 or more

评价:加深迭代的A*算法,本质上就是剪枝,设估价函数的目的就是剪枝了。而难点就是如何设计估价函数。

代码:

import java.util.Arrays;
import java.util.Scanner;

public class Main 
{

    static int a[]=new int[20];
    static int n;
    static boolean check()
    {
        for(int i=0;i<n;i++)
        {
            if(a[i]!=i+1)
                return false;
        }   
        return true;
    }
    static int h()
    {
        int ans=0;
        for(int i=0;i<n-1;i++)
            if(a[i]+1!=a[i+1])ans++;
        if(a[n-1]!=n)ans++;
        return ans;
    }
    static boolean dfs(int d,int maxD)
    {
        if(check())return true;
        if(3*d+h()>3*maxD)return false;
        int b[]=new int[20];
        int tot;
        int last[]=Arrays.copyOf(a,20);
        for(int i=0;i<n;i++)
        {
            for(int j=i;j<n;j++)
            {
                tot=0;
                for(int k=i;k<=j;k++)
                    b[tot++]=last[k];
                for(int k=0;k<n;k++)
                {
                    a=Arrays.copyOf(last, 20);
                    if(k<i)
                    {
                        for(int u=0;u<i-k;u++)
                            a[j-u]=a[i-u-1];
                        for(int u=0;u<tot;u++)
                            a[k+u]=b[u];
                        if(dfs(d+1,maxD))return true;
                    }
                    else
                        if(k>j)
                        {
                            for(int u=0;u<k-j;u++)
                                a[i+u]=a[j+u+1];
                            for(int u=0;u<tot;u++)
                                a[i+k-j+u]=b[u];
                            if(dfs(d+1,maxD))return true;
                        }
                }
            }
        }
        return false;
    }
    static void IDAstar()
    {
        if(check())
        {
            System.out.println(0);
            //System.out.println("hah");
            return ;
        }
        for(int i=1;i<=4;i++)
        {
            if(dfs(0,i)) 
            {
                System.out.println(i);
                return;
            }

        }
        System.out.println("5 or more");
    }
    public static void main(String[] args) 
    {
        Scanner sc=new Scanner(System.in);
        int t=sc.nextInt();
        while(t-->0)
        {
            n=sc.nextInt();
            for(int i=0;i<n;i++)
                a[i]=sc.nextInt();
            IDAstar();
        }
    }
}
这是一道比较经典的计数问题。题目描述如下: 给定一个 $n \times n$ 的网格图,其中一些格子被标记为障碍。一个连通块是指一些被标记为障碍的格子的集合,满足这些格子在网格图中连通。一个格子是连通的当且仅当它与另一个被标记为障碍的格子在网格图中有公共边。 现在,你需要计算在这个网格图中,有多少个不同的连通块,满足这个连通块的大小(即包含的格子数)恰好为 $k$。 这是一道比较经典的计数问题,一般可以通过计算生成函数的方法来解决。具体来说,我们可以定义一个生成函数 $F(x)$,其中 $[x^k]F(x)$ 表示大小为 $k$ 的连通块的个数。那么,我们可以考虑如何计算这个生成函数。 对于一个大小为 $k$ 的连通块,我们可以考虑它的形状。具体来说,我们可以考虑以该连通块的最左边、最上边的格子为起点,从上到下、从左到右遍历该连通块,把每个格子在该连通块中的相对位置记录下来。由于该连通块的大小为 $k$,因此这些相对位置一定是 $(x,y) \in [0,n-1]^2$ 中的 $k$ 个不同点。 现在,我们需要考虑如何计算这些点对应的连通块是否合法。具体来说,我们可以考虑从左到右、从上到下依次处理这些点,对于每个点 $(x,y)$,我们需要考虑它是否能够与左边的点和上边的点连通。具体来说,如果 $(x-1,y)$ 和 $(x,y)$ 都在该连通块中且它们在网格图中有公共边,那么它们就是连通的;同样,如果 $(x,y-1)$ 和 $(x,y)$ 都在该连通块中且它们在网格图中有公共边,那么它们也是连通的。如果 $(x,y)$ 与左边和上边的点都不连通,那么说明这个点不属于该连通块。 考虑到每个点最多只有两个方向需要检查,因此时间复杂度为 $O(n^2 k)$。不过,我们可以使用类似于矩阵乘法的思想,将这个过程优化到 $O(k^3)$ 的时间复杂度。 具体来说,我们可以设 $f_{i,j,k}$ 表示状态 $(i,j)$ 所代表的点在连通块中,且连通块的大小为 $k$ 的方案数。显然,对于一个合法的 $(i,j,k)$,我们可以考虑 $(i-1,j,k-1)$ 和 $(i,j-1,k-1)$ 这两个状态,然后把点 $(i,j)$ 加入到它们所代表的连通块中。因此,我们可以设计一个 $O(k^3)$ 的 DP 状态转移,计算 $f_{i,j,k}$。 具体来说,我们可以考虑枚举连通块所包含的最右边和最下边的格子的坐标 $(x,y)$,然后计算 $f_{x,y,k}$。对于一个合法的 $(x,y,k)$,我们可以考虑将 $(x,y)$ 所代表的点加入到 $(x-1,y,k-1)$ 和 $(x,y-1,k-1)$ 所代表的连通块中。不过,这里需要注意一个细节:如果 $(x-1,y)$ 和 $(x,y)$ 在网格图中没有相邻边,那么它们不能算作连通的。因此,我们需要特判这个情况。 最终,$f_{n,n,k}$ 就是大小为 $k$ 的连通块的个数,时间复杂度为 $O(n^2 k + k^3)$。 参考代码:
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