75

我想生成集合(集合)的所有排列,如下所示:

Collection: 1, 2, 3
Permutations: {1, 2, 3}
              {1, 3, 2}
              {2, 1, 3}
              {2, 3, 1}
              {3, 1, 2}
              {3, 2, 1}

一般来说,这不是“如何”的问题,而是关于如何最有效的问题。另外,我不想生成所有排列并返回它们,而是一次只生成一个排列,并且仅在必要时继续(很像迭代器 - 我也尝试过,但结果更少高效的)。

我测试了许多算法和方法,并提出了这段代码,这是我尝试过的最有效的代码:

public static bool NextPermutation<T>(T[] elements) where T : IComparable<T>
{
    // More efficient to have a variable instead of accessing a property
    var count = elements.Length;

    // Indicates whether this is the last lexicographic permutation
    var done = true;

    // Go through the array from last to first
    for (var i = count - 1; i > 0; i--)
    {
        var curr = elements[i];

        // Check if the current element is less than the one before it
        if (curr.CompareTo(elements[i - 1]) < 0)
        {
            continue;
        }

        // An element bigger than the one before it has been found,
        // so this isn't the last lexicographic permutation.
        done = false;

        // Save the previous (bigger) element in a variable for more efficiency.
        var prev = elements[i - 1];

        // Have a variable to hold the index of the element to swap
        // with the previous element (the to-swap element would be
        // the smallest element that comes after the previous element
        // and is bigger than the previous element), initializing it
        // as the current index of the current item (curr).
        var currIndex = i;

        // Go through the array from the element after the current one to last
        for (var j = i + 1; j < count; j++)
        {
            // Save into variable for more efficiency
            var tmp = elements[j];

            // Check if tmp suits the "next swap" conditions:
            // Smallest, but bigger than the "prev" element
            if (tmp.CompareTo(curr) < 0 && tmp.CompareTo(prev) > 0)
            {
                curr = tmp;
                currIndex = j;
            }
        }

        // Swap the "prev" with the new "curr" (the swap-with element)
        elements[currIndex] = prev;
        elements[i - 1] = curr;

        // Reverse the order of the tail, in order to reset it's lexicographic order
        for (var j = count - 1; j > i; j--, i++)
        {
            var tmp = elements[j];
            elements[j] = elements[i];
            elements[i] = tmp;
        }

        // Break since we have got the next permutation
        // The reason to have all the logic inside the loop is
        // to prevent the need of an extra variable indicating "i" when
        // the next needed swap is found (moving "i" outside the loop is a
        // bad practice, and isn't very readable, so I preferred not doing
        // that as well).
        break;
    }

    // Return whether this has been the last lexicographic permutation.
    return done;
}

它的用法是发送一个元素数组,并返回一个布尔值,指示这是否是最后一个字典排列,以及将数组更改为下一个排列。

使用示例:

var arr = new[] {1, 2, 3};

PrintArray(arr);

while (!NextPermutation(arr))
{
    PrintArray(arr);
}

问题是我对代码的速度不满意。

遍历大小为 11 的数组的所有排列大约需要 4 秒。虽然它可以被认为是令人印象深刻的,因为一组大小为 11 的可能排列的数量11!接近 4000 万。

从逻辑上讲,对于大小为 12 的数组,它将花费大约 12 倍的时间,因为12!is 11! * 12,对于大小为 13 的数组,它将花费大约 13 倍于大小为 12 的时间,依此类推。

所以你可以很容易地理解一个大小为 12 或更大的数组,它确实需要很长时间才能完成所有排列。

而且我有一种强烈的预感,我可以以某种方式将时间缩短很多(无需切换到 C# 以外的语言 - 因为编译器优化确实可以很好地优化,我怀疑我可以在汇编中手动优化)。

有谁知道任何其他方法可以更快地完成这项工作?您对如何使当前算法更快有任何想法吗?

请注意,我不想使用外部库或服务来做到这一点 - 我希望拥有代码本身,并且我希望它尽可能高效。

4

18 回答 18

38

这可能是您正在寻找的。

    private static bool NextPermutation(int[] numList)
    {
        /*
         Knuths
         1. Find the largest index j such that a[j] < a[j + 1]. If no such index exists, the permutation is the last permutation.
         2. Find the largest index l such that a[j] < a[l]. Since j + 1 is such an index, l is well defined and satisfies j < l.
         3. Swap a[j] with a[l].
         4. Reverse the sequence from a[j + 1] up to and including the final element a[n].

         */
        var largestIndex = -1;
        for (var i = numList.Length - 2; i >= 0; i--)
        {
            if (numList[i] < numList[i + 1]) {
                largestIndex = i;
                break;
            }
        }

        if (largestIndex < 0) return false;

        var largestIndex2 = -1;
        for (var i = numList.Length - 1 ; i >= 0; i--) {
            if (numList[largestIndex] < numList[i]) {
                largestIndex2 = i;
                break;
            }
        }

        var tmp = numList[largestIndex];
        numList[largestIndex] = numList[largestIndex2];
        numList[largestIndex2] = tmp;

        for (int i = largestIndex + 1, j = numList.Length - 1; i < j; i++, j--) {
            tmp = numList[i];
            numList[i] = numList[j];
            numList[j] = tmp;
        }

        return true;
    }
于 2012-06-26T13:37:04.030 回答
29

2018 年 5 月 28 日更新:

有点晚了……

根据最近的测试(2018-05-22 更新)

  • 最快的是我的,但不是按字典顺序
  • 对于最快的词典顺序,Sani Singh Huttunen 解决方案似乎是要走的路。

在我的机器上发布的 10 个项目(10 个!)的性能测试结果(毫秒):

  • 欧莱特 : 29
  • 简单变量:95
  • 埃雷兹·罗宾逊:156
  • 萨尼·辛格·胡图宁:37
  • 彭阳:45047

在我的机器上发布的 13 个项目(13 个!)的性能测试结果(秒):

  • 欧莱特:48.437
  • 简单变量:159.869
  • 埃雷兹·罗宾逊:327.781
  • 萨尼辛格胡图宁:64.839

我的解决方案的优点:

  • 堆算法(每个排列的单交换)
  • 没有乘法(就像网上看到的一些实现)
  • 内联交换
  • 通用的
  • 没有不安全的代码
  • 就地(非常低的内存使用)
  • 无模(仅第一位比较)

我对堆算法的实现

using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.Linq;
using System.Runtime.CompilerServices;

namespace WpfPermutations
{
    /// <summary>
    /// EO: 2016-04-14
    /// Generator of all permutations of an array of anything.
    /// Base on Heap's Algorithm. See: https://en.wikipedia.org/wiki/Heap%27s_algorithm#cite_note-3
    /// </summary>
    public static class Permutations
    {
        /// <summary>
        /// Heap's algorithm to find all pmermutations. Non recursive, more efficient.
        /// </summary>
        /// <param name="items">Items to permute in each possible ways</param>
        /// <param name="funcExecuteAndTellIfShouldStop"></param>
        /// <returns>Return true if cancelled</returns> 
        public static bool ForAllPermutation<T>(T[] items, Func<T[], bool> funcExecuteAndTellIfShouldStop)
        {
            int countOfItem = items.Length;

            if (countOfItem <= 1)
            {
                return funcExecuteAndTellIfShouldStop(items);
            }

            var indexes = new int[countOfItem];
            
            // Unecessary. Thanks to NetManage for the advise
            // for (int i = 0; i < countOfItem; i++)
            // {
            //     indexes[i] = 0;
            // }

            if (funcExecuteAndTellIfShouldStop(items))
            {
                return true;
            }

            for (int i = 1; i < countOfItem;)
            {
                if (indexes[i] < i)
                { // On the web there is an implementation with a multiplication which should be less efficient.
                    if ((i & 1) == 1) // if (i % 2 == 1)  ... more efficient ??? At least the same.
                    {
                        Swap(ref items[i], ref items[indexes[i]]);
                    }
                    else
                    {
                        Swap(ref items[i], ref items[0]);
                    }

                    if (funcExecuteAndTellIfShouldStop(items))
                    {
                        return true;
                    }

                    indexes[i]++;
                    i = 1;
                }
                else
                {
                    indexes[i++] = 0;
                }
            }

            return false;
        }

        /// <summary>
        /// This function is to show a linq way but is far less efficient
        /// From: StackOverflow user: Pengyang : http://stackoverflow.com/questions/756055/listing-all-permutations-of-a-string-integer
        /// </summary>
        /// <typeparam name="T"></typeparam>
        /// <param name="list"></param>
        /// <param name="length"></param>
        /// <returns></returns>
        static IEnumerable<IEnumerable<T>> GetPermutations<T>(IEnumerable<T> list, int length)
        {
            if (length == 1) return list.Select(t => new T[] { t });

            return GetPermutations(list, length - 1)
                .SelectMany(t => list.Where(e => !t.Contains(e)),
                    (t1, t2) => t1.Concat(new T[] { t2 }));
        }

        /// <summary>
        /// Swap 2 elements of same type
        /// </summary>
        /// <typeparam name="T"></typeparam>
        /// <param name="a"></param>
        /// <param name="b"></param>
        [MethodImpl(MethodImplOptions.AggressiveInlining)]
        static void Swap<T>(ref T a, ref T b)
        {
            T temp = a;
            a = b;
            b = temp;
        }

        /// <summary>
        /// Func to show how to call. It does a little test for an array of 4 items.
        /// </summary>
        public static void Test()
        {
            ForAllPermutation("123".ToCharArray(), (vals) =>
            {
                Console.WriteLine(String.Join("", vals));
                return false;
            });

            int[] values = new int[] { 0, 1, 2, 4 };

            Console.WriteLine("Ouellet heap's algorithm implementation");
            ForAllPermutation(values, (vals) =>
            {
                Console.WriteLine(String.Join("", vals));
                return false;
            });

            Console.WriteLine("Linq algorithm");
            foreach (var v in GetPermutations(values, values.Length))
            {
                Console.WriteLine(String.Join("", v));
            }

            // Performance Heap's against Linq version : huge differences
            int count = 0;

            values = new int[10];
            for (int n = 0; n < values.Length; n++)
            {
                values[n] = n;
            }

            Stopwatch stopWatch = new Stopwatch();

            ForAllPermutation(values, (vals) =>
            {
                foreach (var v in vals)
                {
                    count++;
                }
                return false;
            });

            stopWatch.Stop();
            Console.WriteLine($"Ouellet heap's algorithm implementation {count} items in {stopWatch.ElapsedMilliseconds} millisecs");

            count = 0;
            stopWatch.Reset();
            stopWatch.Start();

            foreach (var vals in GetPermutations(values, values.Length))
            {
                foreach (var v in vals)
                {
                    count++;
                }
            }

            stopWatch.Stop();
            Console.WriteLine($"Linq {count} items in {stopWatch.ElapsedMilliseconds} millisecs");
        }
    }
}

这是我的测试代码:

Task.Run(() =>
            {

                int[] values = new int[12];
                for (int n = 0; n < values.Length; n++)
                {
                    values[n] = n;
                }

                // Eric Ouellet Algorithm
                int count = 0;
                var stopwatch = new Stopwatch();
                stopwatch.Reset();
                stopwatch.Start();
                Permutations.ForAllPermutation(values, (vals) =>
                {
                    foreach (var v in vals)
                    {
                        count++;
                    }
                    return false;
                });
                stopwatch.Stop();
                Console.WriteLine($"This {count} items in {stopwatch.ElapsedMilliseconds} millisecs");

                // Simple Plan Algorithm
                count = 0;
                stopwatch.Reset();
                stopwatch.Start();
                PermutationsSimpleVar permutations2 = new PermutationsSimpleVar();
                permutations2.Permutate(1, values.Length, (int[] vals) =>
                {
                    foreach (var v in vals)
                    {
                        count++;
                    }
                });
                stopwatch.Stop();
                Console.WriteLine($"Simple Plan {count} items in {stopwatch.ElapsedMilliseconds} millisecs");

                // ErezRobinson Algorithm
                count = 0;
                stopwatch.Reset();
                stopwatch.Start();
                foreach(var vals in PermutationsErezRobinson.QuickPerm(values))
                {
                    foreach (var v in vals)
                    {
                        count++;
                    }
                };
                stopwatch.Stop();
                Console.WriteLine($"Erez Robinson {count} items in {stopwatch.ElapsedMilliseconds} millisecs");
            });

使用示例:

ForAllPermutation("123".ToCharArray(), (vals) =>
    {
        Console.WriteLine(String.Join("", vals));
        return false;
    });

int[] values = new int[] { 0, 1, 2, 4 };
ForAllPermutation(values, (vals) =>
        {
            Console.WriteLine(String.Join("", vals));
            return false;
        });
于 2016-04-14T22:13:18.383 回答
12

好吧,如果你可以用 C 语言处理它,然后翻译成你选择的语言,你真的不能比这快得多,因为时间将由以下因素支配print

void perm(char* s, int n, int i){
  if (i >= n-1) print(s);
  else {
    perm(s, n, i+1);
    for (int j = i+1; j<n; j++){
      swap(s[i], s[j]);
      perm(s, n, i+1);
      swap(s[i], s[j]);
    }
  }
}

perm("ABC", 3, 0);
于 2012-06-26T18:23:53.190 回答
8

我所知道的最快的置换算法是 QuickPerm 算法。
这是实现,它使用 yield return 因此您可以根据需要一次迭代一个。

代码:

public static IEnumerable<IEnumerable<T>> QuickPerm<T>(this IEnumerable<T> set)
    {
        int N = set.Count();
        int[] a = new int[N];
        int[] p = new int[N];

        var yieldRet = new T[N];

        List<T> list = new List<T>(set);

        int i, j, tmp; // Upper Index i; Lower Index j

        for (i = 0; i < N; i++)
        {
            // initialize arrays; a[N] can be any type
            a[i] = i + 1; // a[i] value is not revealed and can be arbitrary
            p[i] = 0; // p[i] == i controls iteration and index boundaries for i
        }
        yield return list;
        //display(a, 0, 0);   // remove comment to display array a[]
        i = 1; // setup first swap points to be 1 and 0 respectively (i & j)
        while (i < N)
        {
            if (p[i] < i)
            {
                j = i%2*p[i]; // IF i is odd then j = p[i] otherwise j = 0
                tmp = a[j]; // swap(a[j], a[i])
                a[j] = a[i];
                a[i] = tmp;

                //MAIN!

                for (int x = 0; x < N; x++)
                {
                    yieldRet[x] = list[a[x]-1];
                }
                yield return yieldRet;
                //display(a, j, i); // remove comment to display target array a[]

                // MAIN!

                p[i]++; // increase index "weight" for i by one
                i = 1; // reset index i to 1 (assumed)
            }
            else
            {
                // otherwise p[i] == i
                p[i] = 0; // reset p[i] to zero
                i++; // set new index value for i (increase by one)
            } // if (p[i] < i)
        } // while(i < N)
    }
于 2012-06-26T13:49:24.013 回答
7

2018-05-28更新,新版本,最快...(多线程)

在此处输入图像描述

                            Time taken for fastest algorithms

需要:Sani Singh Huttunen(最快的词典)解决方案和我的支持索引的新 OuelletLexico3

索引有两个主要优点:

  • 允许直接获得任何人的排列
  • 允许多线程(源自第一个优势)

文章:排列:快速实现和允许多线程的新索引算法

在我的机器上(6 个超线程内核:12 个线程)Xeon E5-1660 0 @ 3.30Ghz,测试运行 13 个空东西的算法!项目(以毫秒为单位的时间):

  • 53071:Ouellet(堆的实现)
  • 65366:Sani Singh Huttunen(最快的词汇)
  • 11377:混合 OuelletLexico3 - Sani Singh Huttunen

附注:如果它们的使用是修改(读/写),则在线程之间使用共享属性/变量进行排列操作将强烈影响性能。这样做会在线程之间产生“错误共享”。您将无法获得预期的性能。我在测试时遇到了这种行为。当我尝试增加置换总数的全局变量时,我的经验显示出问题。

用法:

PermutationMixOuelletSaniSinghHuttunen.ExecuteForEachPermutationMT(
  new int[] {1, 2, 3, 4}, 
  p => 
    { 
      Console.WriteLine($"Values: {p[0]}, {p[1]}, p[2]}, {p[3]}"); 
    });

代码:

using System;
using System.Runtime.CompilerServices;

namespace WpfPermutations
{
    public class Factorial
    {
        // ************************************************************************
        protected static long[] FactorialTable = new long[21];

        // ************************************************************************
        static Factorial()
        {
            FactorialTable[0] = 1; // To prevent divide by 0
            long f = 1;
            for (int i = 1; i <= 20; i++)
            {
                f = f * i;
                FactorialTable[i] = f;
            }
        }

        // ************************************************************************
        [MethodImpl(MethodImplOptions.AggressiveInlining)]
        public static long GetFactorial(int val) // a long can only support up to 20!
        {
            if (val > 20)
            {
                throw new OverflowException($"{nameof(Factorial)} only support a factorial value <= 20");
            }

            return FactorialTable[val];
        }

        // ************************************************************************

    }
}


namespace WpfPermutations
{
    public class PermutationSaniSinghHuttunen
    {
        public static bool NextPermutation(int[] numList)
        {
            /*
             Knuths
             1. Find the largest index j such that a[j] < a[j + 1]. If no such index exists, the permutation is the last permutation.
             2. Find the largest index l such that a[j] < a[l]. Since j + 1 is such an index, l is well defined and satisfies j < l.
             3. Swap a[j] with a[l].
             4. Reverse the sequence from a[j + 1] up to and including the final element a[n].

             */
            var largestIndex = -1;
            for (var i = numList.Length - 2; i >= 0; i--)
            {
                if (numList[i] < numList[i + 1])
                {
                    largestIndex = i;
                    break;
                }
            }

            if (largestIndex < 0) return false;

            var largestIndex2 = -1;
            for (var i = numList.Length - 1; i >= 0; i--)
            {
                if (numList[largestIndex] < numList[i])
                {
                    largestIndex2 = i;
                    break;
                }
            }

            var tmp = numList[largestIndex];
            numList[largestIndex] = numList[largestIndex2];
            numList[largestIndex2] = tmp;

            for (int i = largestIndex + 1, j = numList.Length - 1; i < j; i++, j--)
            {
                tmp = numList[i];
                numList[i] = numList[j];
                numList[j] = tmp;
            }

            return true;
        }
    }
}


using System;

namespace WpfPermutations
{
    public class PermutationOuelletLexico3<T> // Enable indexing 
    {
        // ************************************************************************
        private T[] _sortedValues;

        private bool[] _valueUsed;

        public readonly long MaxIndex; // long to support 20! or less 

        // ************************************************************************
        public PermutationOuelletLexico3(T[] sortedValues)
        {
            _sortedValues = sortedValues;
            Result = new T[_sortedValues.Length];
            _valueUsed = new bool[_sortedValues.Length];

            MaxIndex = Factorial.GetFactorial(_sortedValues.Length);
        }

        // ************************************************************************
        public T[] Result { get; private set; }

        // ************************************************************************
        /// <summary>
        /// Sort Index is 0 based and should be less than MaxIndex. Otherwise you get an exception.
        /// </summary>
        /// <param name="sortIndex"></param>
        /// <param name="result">Value is not used as inpu, only as output. Re-use buffer in order to save memory</param>
        /// <returns></returns>
        public void GetSortedValuesFor(long sortIndex)
        {
            int size = _sortedValues.Length;

            if (sortIndex < 0)
            {
                throw new ArgumentException("sortIndex should greater or equal to 0.");
            }

            if (sortIndex >= MaxIndex)
            {
                throw new ArgumentException("sortIndex should less than factorial(the lenght of items)");
            }

            for (int n = 0; n < _valueUsed.Length; n++)
            {
                _valueUsed[n] = false;
            }

            long factorielLower = MaxIndex;

            for (int index = 0; index < size; index++)
            {
                long factorielBigger = factorielLower;
                factorielLower = Factorial.GetFactorial(size - index - 1);  //  factorielBigger / inverseIndex;

                int resultItemIndex = (int)(sortIndex % factorielBigger / factorielLower);

                int correctedResultItemIndex = 0;
                for(;;)
                {
                    if (! _valueUsed[correctedResultItemIndex])
                    {
                        resultItemIndex--;
                        if (resultItemIndex < 0)
                        {
                            break;
                        }
                    }
                    correctedResultItemIndex++;
                }

                Result[index] = _sortedValues[correctedResultItemIndex];
                _valueUsed[correctedResultItemIndex] = true;
            }
        }

        // ************************************************************************
    }
}


using System;
using System.Collections.Generic;
using System.Threading.Tasks;

namespace WpfPermutations
{
    public class PermutationMixOuelletSaniSinghHuttunen
    {
        // ************************************************************************
        private long _indexFirst;
        private long _indexLastExclusive;
        private int[] _sortedValues;

        // ************************************************************************
        public PermutationMixOuelletSaniSinghHuttunen(int[] sortedValues, long indexFirst = -1, long indexLastExclusive = -1)
        {
            if (indexFirst == -1)
            {
                indexFirst = 0;
            }

            if (indexLastExclusive == -1)
            {
                indexLastExclusive = Factorial.GetFactorial(sortedValues.Length);
            }

            if (indexFirst >= indexLastExclusive)
            {
                throw new ArgumentException($"{nameof(indexFirst)} should be less than {nameof(indexLastExclusive)}");
            }

            _indexFirst = indexFirst;
            _indexLastExclusive = indexLastExclusive;
            _sortedValues = sortedValues;
        }

        // ************************************************************************
        public void ExecuteForEachPermutation(Action<int[]> action)
        {
            //          Console.WriteLine($"Thread {System.Threading.Thread.CurrentThread.ManagedThreadId} started: {_indexFirst} {_indexLastExclusive}");

            long index = _indexFirst;

            PermutationOuelletLexico3<int> permutationOuellet = new PermutationOuelletLexico3<int>(_sortedValues);

            permutationOuellet.GetSortedValuesFor(index);
            action(permutationOuellet.Result);
            index++;

            int[] values = permutationOuellet.Result;
            while (index < _indexLastExclusive)
            {
                PermutationSaniSinghHuttunen.NextPermutation(values);
                action(values);
                index++;
            }

            //          Console.WriteLine($"Thread {System.Threading.Thread.CurrentThread.ManagedThreadId} ended: {DateTime.Now.ToString("yyyyMMdd_HHmmss_ffffff")}");
        }

        // ************************************************************************
        public static void ExecuteForEachPermutationMT(int[] sortedValues, Action<int[]> action)
        {
            int coreCount = Environment.ProcessorCount; // Hyper treading are taken into account (ex: on a 4 cores hyperthreaded = 8)
            long itemsFactorial = Factorial.GetFactorial(sortedValues.Length);
            long partCount = (long)Math.Ceiling((double)itemsFactorial / (double)coreCount);
            long startIndex = 0;

            var tasks = new List<Task>();

            for (int coreIndex = 0; coreIndex < coreCount; coreIndex++)
            {
                long stopIndex = Math.Min(startIndex + partCount, itemsFactorial);

                PermutationMixOuelletSaniSinghHuttunen mix = new PermutationMixOuelletSaniSinghHuttunen(sortedValues, startIndex, stopIndex);
                Task task = Task.Run(() => mix.ExecuteForEachPermutation(action));
                tasks.Add(task);

                if (stopIndex == itemsFactorial)
                {
                    break;
                }

                startIndex = startIndex + partCount;
            }

            Task.WaitAll(tasks.ToArray());
        }

        // ************************************************************************


    }
}
于 2018-05-28T15:32:49.500 回答
4

这是我最终得到的最快的实现:

public class Permutations
{
    private readonly Mutex _mutex = new Mutex();

    private Action<int[]> _action;
    private Action<IntPtr> _actionUnsafe;
    private unsafe int* _arr;
    private IntPtr _arrIntPtr;
    private unsafe int* _last;
    private unsafe int* _lastPrev;
    private unsafe int* _lastPrevPrev;

    public int Size { get; private set; }

    public bool IsRunning()
    {
        return this._mutex.SafeWaitHandle.IsClosed;
    }

    public bool Permutate(int start, int count, Action<int[]> action, bool async = false)
    {
        return this.Permutate(start, count, action, null, async);
    }

    public bool Permutate(int start, int count, Action<IntPtr> actionUnsafe, bool async = false)
    {
        return this.Permutate(start, count, null, actionUnsafe, async);
    }

    private unsafe bool Permutate(int start, int count, Action<int[]> action, Action<IntPtr> actionUnsafe, bool async = false)
    {
        if (!this._mutex.WaitOne(0))
        {
            return false;
        }

        var x = (Action)(() =>
                             {
                                 this._actionUnsafe = actionUnsafe;
                                 this._action = action;

                                 this.Size = count;

                                 this._arr = (int*)Marshal.AllocHGlobal(count * sizeof(int));
                                 this._arrIntPtr = new IntPtr(this._arr);

                                 for (var i = 0; i < count - 3; i++)
                                 {
                                     this._arr[i] = start + i;
                                 }

                                 this._last = this._arr + count - 1;
                                 this._lastPrev = this._last - 1;
                                 this._lastPrevPrev = this._lastPrev - 1;

                                 *this._last = count - 1;
                                 *this._lastPrev = count - 2;
                                 *this._lastPrevPrev = count - 3;

                                 this.Permutate(count, this._arr);
                             });

        if (!async)
        {
            x();
        }
        else
        {
            new Thread(() => x()).Start();
        }

        return true;
    }

    private unsafe void Permutate(int size, int* start)
    {
        if (size == 3)
        {
            this.DoAction();
            Swap(this._last, this._lastPrev);
            this.DoAction();
            Swap(this._last, this._lastPrevPrev);
            this.DoAction();
            Swap(this._last, this._lastPrev);
            this.DoAction();
            Swap(this._last, this._lastPrevPrev);
            this.DoAction();
            Swap(this._last, this._lastPrev);
            this.DoAction();

            return;
        }

        var sizeDec = size - 1;
        var startNext = start + 1;
        var usedStarters = 0;

        for (var i = 0; i < sizeDec; i++)
        {
            this.Permutate(sizeDec, startNext);

            usedStarters |= 1 << *start;

            for (var j = startNext; j <= this._last; j++)
            {
                var mask = 1 << *j;

                if ((usedStarters & mask) != mask)
                {
                    Swap(start, j);
                    break;
                }
            }
        }

        this.Permutate(sizeDec, startNext);

        if (size == this.Size)
        {
            this._mutex.ReleaseMutex();
        }
    }

    private unsafe void DoAction()
    {
        if (this._action == null)
        {
            if (this._actionUnsafe != null)
            {
                this._actionUnsafe(this._arrIntPtr);
            }

            return;
        }

        var result = new int[this.Size];

        fixed (int* pt = result)
        {
            var limit = pt + this.Size;
            var resultPtr = pt;
            var arrayPtr = this._arr;

            while (resultPtr < limit)
            {
                *resultPtr = *arrayPtr;
                resultPtr++;
                arrayPtr++;
            }
        }

        this._action(result);
    }

    private static unsafe void Swap(int* a, int* b)
    {
        var tmp = *a;
        *a = *b;
        *b = tmp;
    }
}

使用及测试性能:

var perms = new Permutations();

var sw1 = Stopwatch.StartNew();

perms.Permutate(0,
                11,
                (Action<int[]>)null); // Comment this line and...
                //PrintArr); // Uncomment this line, to print permutations

sw1.Stop();
Console.WriteLine(sw1.Elapsed);

印刷方式:

private static void PrintArr(int[] arr)
{
    Console.WriteLine(string.Join(",", arr));
}

更深入:

我什至没有考虑这个问题很长时间,所以我只能解释我的代码,但这里是大致的想法:

  1. 排列不是字典顺序的——这使我实际上可以在排列之间执行更少的操作。
  2. 该实现是递归的,当“视图”大小为 3 时,它会跳过复杂的逻辑并只执行 6 次交换以获得 6 个排列(或子排列,如果你愿意的话)。
  3. 因为排列不是按字典顺序排列的,我如何决定将哪个元素带到当前“视图”(子排列)的开头?我记录了在当前子排列递归调用中已经用作“启动器”的元素,并简单地线性搜索未在我的数组尾部使用的元素。
  4. 该实现仅适用于整数,因此要对通用元素集合进行置换,您只需使用 Permutations 类来置换索引而不是实际集合。
  5. 互斥锁只是为了确保在异步执行时事情不会搞砸(请注意,您可以传递一个 UnsafeAction 参数,该参数反过来会获得一个指向置换数组的指针。您不能更改该数组中元素的顺序(指针)!如果你愿意,你应该将数组复制到一个 tmp 数组,或者只使用为你处理的安全操作参数 - 传递的数组已经是一个副本)。

笔记:

我不知道这个实现到底有多好——我很久没碰过它了。自行测试并与其他实现进行比较,如果您有任何反馈,请告诉我!

享受。

于 2014-07-20T15:34:21.253 回答
3

这是一个通用排列查找器,它将遍历集合的每个排列并调用评估函数。如果评估函数返回 true(它找到了它正在寻找的答案),则排列查找器停止处理。

public class PermutationFinder<T>
{
    private T[] items;
    private Predicate<T[]> SuccessFunc;
    private bool success = false;
    private int itemsCount;

    public void Evaluate(T[] items, Predicate<T[]> SuccessFunc)
    {
        this.items = items;
        this.SuccessFunc = SuccessFunc;
        this.itemsCount = items.Count();

        Recurse(0);
    }

    private void Recurse(int index)
    {
        T tmp;

        if (index == itemsCount)
            success = SuccessFunc(items);
        else
        {
            for (int i = index; i < itemsCount; i++)
            {
                tmp = items[index];
                items[index] = items[i];
                items[i] = tmp;

                Recurse(index + 1);

                if (success)
                    break;

                tmp = items[index];
                items[index] = items[i];
                items[i] = tmp;
            }
        }
    }
}

这是一个简单的实现:

class Program
{
    static void Main(string[] args)
    {
        new Program().Start();
    }

    void Start()
    {
        string[] items = new string[5];
        items[0] = "A";
        items[1] = "B";
        items[2] = "C";
        items[3] = "D";
        items[4] = "E";
        new PermutationFinder<string>().Evaluate(items, Evaluate);
        Console.ReadLine();
    }

    public bool Evaluate(string[] items)
    {
        Console.WriteLine(string.Format("{0},{1},{2},{3},{4}", items[0], items[1], items[2], items[3], items[4]));
        bool someCondition = false;

        if (someCondition)
            return true;  // Tell the permutation finder to stop.

        return false;
    }
}
于 2013-06-17T19:00:23.413 回答
2

这是一个基于交换数组元素的复杂度为O(n * n!)1的递归实现。该数组使用来自 的值进行初始化1, 2, ..., n

using System;

namespace Exercise
{
class Permutations
{
    static void Main(string[] args)
    {
        int setSize = 3;
        FindPermutations(setSize);
    }
    //-----------------------------------------------------------------------------
    /* Method: FindPermutations(n) */
    private static void FindPermutations(int n)
    {
        int[] arr = new int[n];
        for (int i = 0; i < n; i++)
        {
            arr[i] = i + 1;
        }
        int iEnd = arr.Length - 1;
        Permute(arr, iEnd);
    }
    //-----------------------------------------------------------------------------  
    /* Method: Permute(arr) */
    private static void Permute(int[] arr, int iEnd)
    {
        if (iEnd == 0)
        {
            PrintArray(arr);
            return;
        }

        Permute(arr, iEnd - 1);
        for (int i = 0; i < iEnd; i++)
        {
            swap(ref arr[i], ref arr[iEnd]);
            Permute(arr, iEnd - 1);
            swap(ref arr[i], ref arr[iEnd]);
        }
    }
}
}

在每个递归步骤中,我们将最后一个元素与循环中的局部变量指向的当前元素交换for,然后我们通过以下方式指示交换的唯一性:增加循环的局部变量for并减少循环的终止条件for,这最初设置为数组中元素的数量,当后者变为零时,我们终止递归。

以下是辅助函数:

    //-----------------------------------------------------------------------------
    /*
        Method: PrintArray()

    */
    private static void PrintArray(int[] arr, string label = "")
    {
        Console.WriteLine(label);
        Console.Write("{");
        for (int i = 0; i < arr.Length; i++)
        {
            Console.Write(arr[i]);
            if (i < arr.Length - 1)
            {
                Console.Write(", ");
            }
        }
        Console.WriteLine("}");
    }
    //-----------------------------------------------------------------------------

    /*
        Method: swap(ref int a, ref int b)

    */
    private static void swap(ref int a, ref int b)
    {
        int temp = a;
        a = b;
        b = temp;
    }

1.要打印的元素有n!排列。n

于 2016-10-13T18:48:06.960 回答
1

在 Steven Skiena 的算法设计手册(第二版第 14.4 章)中有对算法和实现调查的易于理解的介绍

Skiena 引用 D. Knuth。计算机编程艺术,第 4 卷分册 2:生成所有元组和排列。艾迪生卫斯理,2005 年。

于 2012-06-26T14:11:52.963 回答
1

如果真的发现了数量级的改进,我会感到惊讶。如果有,那么 C# 需要从根本上改进。此外,用你的排列做任何有趣的事情通常比生成它需要更多的工作。因此,在整体方案中,发电成本将是微不足道的。

也就是说,我建议尝试以下方法。您已经尝试过迭代器。但是您是否尝试过使用一个将闭包作为输入的函数,然后为找到的每个排列调用该闭包?根据 C# 的内部机制,这可能会更快。

类似地,您是否尝试过使用一个返回闭包的函数,该闭包将迭代特定的排列?

无论使用哪种方法,您都可以尝试许多微优化。例如,您可以对输入数组进行排序,然后您始终知道它的顺序。例如,您可以拥有一个布尔数组,指示该元素是否小于下一个元素,而不是进行比较,您可以看看那个数组。

于 2012-06-26T14:56:47.563 回答
1

我创建了一个比 Knuth 的算法稍快的算法:

11个元素:

我的:0.39 秒

克努斯:0.624 秒

13个元素:

我的:56.615 秒

克努斯:98.681 秒

这是我的Java代码:

public static void main(String[] args)
{
    int n=11;
    int a,b,c,i,tmp;
    int end=(int)Math.floor(n/2);
    int[][] pos = new int[end+1][2];
    int[] perm = new int[n];

    for(i=0;i<n;i++) perm[i]=i;

    while(true)
    {
        //this is where you can use the permutations (perm)
        i=0;
        c=n;

        while(pos[i][1]==c-2 && pos[i][0]==c-1)
        {
            pos[i][0]=0;
            pos[i][1]=0;
            i++;
            c-=2;
        }

        if(i==end) System.exit(0);

        a=(pos[i][0]+1)%c+i;
        b=pos[i][0]+i;

        tmp=perm[b];
        perm[b]=perm[a];
        perm[a]=tmp;

        if(pos[i][0]==c-1)
        {
            pos[i][0]=0;
            pos[i][1]++;
        }
        else
        {
            pos[i][0]++;
        }
    }
}

问题是我的算法只适用于奇数个元素。我很快写了这段代码,所以我很确定有更好的方法来实现我的想法以获得更好的性能,但我现在真的没有时间去优化它并解决问题元素是均匀的。

它是每个排列的一次交换,它使用一种非常简单的方法来知道要交换哪些元素。

我在我的博客上写了代码背后的方法的解释:http: //antoinecomeau.blogspot.ca/2015/01/fast-generation-of-all-permutations.html

于 2015-01-27T03:28:17.677 回答
1

正如这个问题的作者所问的算法:

[...] 一次生成一个排列,并且仅在必要时继续

我建议考虑 Steinhaus-Johnson-Trotter 算法。

维基百科上的 Steinhaus-Johnson-Trotter 算法

这里解释得很漂亮

于 2017-01-03T13:37:18.317 回答
0

现在是凌晨 1 点,我正在看电视并想到了同样的问题,但使用了字符串值。

给定一个单词,找出所有排列。您可以轻松地对其进行修改以处理数组、集合等。

我花了一点时间来解决这个问题,但我想出的解决方案是:

string word = "abcd";

List<string> combinations = new List<string>();

for(int i=0; i<word.Length; i++)
{
    for (int j = 0; j < word.Length; j++)
    {
        if (i < j)
            combinations.Add(word[i] + word.Substring(j) + word.Substring(0, i) + word.Substring(i + 1, j - (i + 1)));
        else if (i > j)
        {
            if(i== word.Length -1)
                combinations.Add(word[i] + word.Substring(0, i));
            else
                combinations.Add(word[i] + word.Substring(0, i) + word.Substring(i + 1));
        }
    }
}

这是与上面相同的代码,但有一些注释

string word = "abcd";

List<string> combinations = new List<string>();

//i is the first letter of the new word combination
for(int i=0; i<word.Length; i++)
{
    for (int j = 0; j < word.Length; j++)
    {
        //add the first letter of the word, j is past i so we can get all the letters from j to the end
        //then add all the letters from the front to i, then skip over i (since we already added that as the beginning of the word)
        //and get the remaining letters from i+1 to right before j.
        if (i < j)
            combinations.Add(word[i] + word.Substring(j) + word.Substring(0, i) + word.Substring(i + 1, j - (i + 1)));
        else if (i > j)
        {
            //if we're at the very last word no need to get the letters after i
            if(i== word.Length -1)
                combinations.Add(word[i] + word.Substring(0, i));
            //add i as the first letter of the word, then get all the letters up to i, skip i, and then add all the lettes after i
            else
                combinations.Add(word[i] + word.Substring(0, i) + word.Substring(i + 1));

        }
    }
}
于 2017-01-24T09:54:08.953 回答
0

我在 Rosetta 代码上找到了这个算法,它确实是我尝试过的最快的算法。http://rosettacode.org/wiki/Permutations#C

/* Boothroyd method; exactly N! swaps, about as fast as it gets */
void boothroyd(int *x, int n, int nn, int callback(int *, int))
{
	int c = 0, i, t;
	while (1) {
		if (n > 2) boothroyd(x, n - 1, nn, callback);
		if (c >= n - 1) return;
 
		i = (n & 1) ? 0 : c;
		c++;
		t = x[n - 1], x[n - 1] = x[i], x[i] = t;
		if (callback) callback(x, nn);
	}
}
 
/* entry for Boothroyd method */
void perm2(int *x, int n, int callback(int*, int))
{
	if (callback) callback(x, n);
	boothroyd(x, n, n, callback);
}
 

于 2018-02-21T23:14:59.283 回答
0

//+------------------------------------------------------------------+
//|                                                                  |
//+------------------------------------------------------------------+
/**
 * http://marknelson.us/2002/03/01/next-permutation/
 * Rearranges the elements into the lexicographically next greater permutation and returns true.
 * When there are no more greater permutations left, the function eventually returns false.
 */

// next lexicographical permutation

template <typename T>
bool next_permutation(T &arr[], int firstIndex, int lastIndex)
{
    int i = lastIndex;
    while (i > firstIndex)
    {
        int ii = i--;
        T curr = arr[i];
        if (curr < arr[ii])
        {
            int j = lastIndex;
            while (arr[j] <= curr) j--;
            Swap(arr[i], arr[j]);
            while (ii < lastIndex)
                Swap(arr[ii++], arr[lastIndex--]);
            return true;
        }
    }
    return false;
}

//+------------------------------------------------------------------+
//|                                                                  |
//+------------------------------------------------------------------+
/**
 * Swaps two variables or two array elements.
 * using references/pointers to speed up swapping.
 */
template<typename T>
void Swap(T &var1, T &var2)
{
    T temp;
    temp = var1;
    var1 = var2;
    var2 = temp;
}

//+------------------------------------------------------------------+
//|                                                                  |
//+------------------------------------------------------------------+
// driver program to test above function
#define N 3

void OnStart()
{
    int i, x[N];
    for (i = 0; i < N; i++) x[i] = i + 1;

    printf("The %i! possible permutations with %i elements:", N, N);

    do
    {
        printf("%s", ArrayToString(x));

    } while (next_permutation(x, 0, N - 1));

}

// Output:
// The 3! possible permutations with 3 elements:
// "1,2,3"
// "1,3,2"
// "2,1,3"
// "2,3,1"
// "3,1,2"
// "3,2,1"

于 2018-02-24T02:08:45.730 回答
0

// Permutations are the different ordered arrangements of an n-element
// array. An n-element array has exactly n! full-length permutations.

// This iterator object allows to iterate all full length permutations
// one by one of an array of n distinct elements.

// The iterator changes the given array in-place.

// Permutations('ABCD') => ABCD  DBAC  ACDB  DCBA
//                         BACD  BDAC  CADB  CDBA
//                         CABD  ADBC  DACB  BDCA
//                         ACBD  DABC  ADCB  DBCA
//                         BCAD  BADC  CDAB  CBDA
//                         CBAD  ABDC  DCAB  BCDA

// count of permutations = n!

// Heap's algorithm (Single swap per permutation)
// http://www.quickperm.org/quickperm.php
// https://stackoverflow.com/a/36634935/4208440
// https://en.wikipedia.org/wiki/Heap%27s_algorithm


// My implementation of Heap's algorithm:

template<typename T>
class PermutationsIterator
{
	int b, e, n;
	int c[32];  /* control array: mixed radix number in rising factorial base.
	            the i-th digit has base i, which means that the digit must be
	            strictly less than i. The first digit is always 0,  the second
	            can be 0 or 1, the third 0, 1 or 2, and so on.
	            ArrayResize isn't strictly necessary, int c[32] would suffice
	            for most practical purposes. Also, it is much faster */

public:
	PermutationsIterator(T &arr[], int firstIndex, int lastIndex)
	{
		this.b = firstIndex;  // v.begin()
		this.e = lastIndex;   // v.end()
		this.n = e - b + 1;

		ArrayInitialize(c, 0);
	}

	// Rearranges the input array into the next permutation and returns true.
	// When there are no more permutations left, the function returns false.

	bool next(T &arr[])
	{
		// find index to update
		int i = 1;

		// reset all the previous indices that reached the maximum possible values
		while (c[i] == i)
		{
			c[i] = 0;
			++i;
		}

		// no more permutations left
		if (i == n)
			return false;

		// generate next permutation
		int j = (i & 1) == 1 ? c[i] : 0;    // IF i is odd then j = c[i] otherwise j = 0.
		swap(arr[b + j], arr[b + i]);       // generate a new permutation from previous permutation using a single swap

		// Increment that index
		++c[i];
		return true;
	}

};

于 2018-03-31T04:25:28.240 回答
-2

如果您只想计算可能的排列数量,您可以避免上面的所有艰苦工作并使用类似的东西(在 c# 中设计):

public static class ContrivedUtils 
{
    public static Int64 Permutations(char[] array)
    {
        if (null == array || array.Length == 0) return 0;

        Int64 permutations = array.Length;

        for (var pos = permutations; pos > 1; pos--)
            permutations *= pos - 1;

        return permutations;
    }
}

你这样称呼它:

var permutations = ContrivedUtils.Permutations("1234".ToCharArray());
// output is: 24
var permutations = ContrivedUtils.Permutations("123456789".ToCharArray());
// output is: 362880
于 2015-02-05T18:57:06.370 回答
-2

通过交换的简单 C# 递归解决方案,对于初始调用,索引必须为 0

    static public void Permute<T>(List<T> input, List<List<T>> permutations, int index)
    {
        if (index == input.Count - 1)
        {
            permutations.Add(new List<T>(input));
            return;
        }

        Permute(input, permutations, index + 1);

        for (int i = index+1 ; i < input.Count; i++)
        {
            //swap
            T temp = input[index];
            input[index] = input[i];
            input[i] = temp;

            Permute(input, permutations, index + 1);

            //swap back
            temp = input[index];
            input[index] = input[i];
            input[i] = temp;
        }
    }
于 2020-09-25T15:02:02.363 回答