我正在为PHP寻找类似的解决方案，遇到了以下情况

class Combinations implements Iterator
{
    protected $c = null;
    protected $s = null;
    protected $n = 0;
    protected $k = 0;
    protected $pos = 0;

    function __construct($s, $k) {
        if(is_array($s)) {
            $this->s = array_values($s);
            $this->n = count($this->s);
        } else {
            $this->s = (string) $s;
            $this->n = strlen($this->s);
        }
        $this->k = $k;
        $this->rewind();
    }
    function key() {
        return $this->pos;
    }
    function current() {
        $r = array();
        for($i = 0; $i < $this->k; $i++)
            $r[] = $this->s[$this->c[$i]];
        return is_array($this->s) ? $r : implode('', $r);
    }
    function next() {
        if($this->_next())
            $this->pos++;
        else
            $this->pos = -1;
    }
    function rewind() {
        $this->c = range(0, $this->k);
        $this->pos = 0;
    }
    function valid() {
        return $this->pos >= 0;
    }

    protected function _next() {
        $i = $this->k - 1;
        while ($i >= 0 && $this->c[$i] == $this->n - $this->k + $i)
            $i--;
        if($i < 0)
            return false;
        $this->c[$i]++;
        while($i++ < $this->k - 1)
            $this->c[$i] = $this->c[$i - 1] + 1;
        return true;
    }
}


foreach(new Combinations("1234567", 5) as $substring)
    echo $substring, ' ';

源

我不确定这个类有多高效，但我只是把它用作种子程序。

下面是Clojure版本，它使用了我在OCaml实现答案中描述的相同算法:

(defn select
  ([items]
     (select items 0 (inc (count items))))
  ([items n1 n2]
     (reduce concat
             (map #(select % items)
                  (range n1 (inc n2)))))
  ([n items]
     (let [
           lmul (fn [a list-of-lists-of-bs]
                     (map #(cons a %) list-of-lists-of-bs))
           ]
       (if (= n (count items))
         (list items)
         (if (empty? items)
           items
           (concat
            (select n (rest items))
            (lmul (first items) (select (dec n) (rest items))))))))) 

它提供了三种调用方法:

(a)按问题要求，选出n项:

  user=> (count (select 3 "abcdefgh"))
  56

(b) n1至n2个选定项目:

user=> (select '(1 2 3 4) 2 3)
((3 4) (2 4) (2 3) (1 4) (1 3) (1 2) (2 3 4) (1 3 4) (1 2 4) (1 2 3))

(c)在0至所选项目的集合大小之间:

user=> (select '(1 2 3))
(() (3) (2) (1) (2 3) (1 3) (1 2) (1 2 3))

短快C实现

#include <stdio.h>

void main(int argc, char *argv[]) {
  const int n = 6; /* The size of the set; for {1, 2, 3, 4} it's 4 */
  const int p = 4; /* The size of the subsets; for {1, 2}, {1, 3}, ... it's 2 */
  int comb[40] = {0}; /* comb[i] is the index of the i-th element in the combination */

  int i = 0;
  for (int j = 0; j <= n; j++) comb[j] = 0;
  while (i >= 0) {
    if (comb[i] < n + i - p + 1) {
       comb[i]++;
       if (i == p - 1) { for (int j = 0; j < p; j++) printf("%d ", comb[j]); printf("\n"); }
       else            { comb[++i] = comb[i - 1]; }
    } else i--; }
}

要查看它有多快，请使用这段代码并测试它

#include <time.h>
#include <stdio.h>

void main(int argc, char *argv[]) {
  const int n = 32; /* The size of the set; for {1, 2, 3, 4} it's 4 */
  const int p = 16; /* The size of the subsets; for {1, 2}, {1, 3}, ... it's 2 */
  int comb[40] = {0}; /* comb[i] is the index of the i-th element in the combination */

  int c = 0; int i = 0;
  for (int j = 0; j <= n; j++) comb[j] = 0;
  while (i >= 0) {
    if (comb[i] < n + i - p + 1) {
       comb[i]++;
       /* if (i == p - 1) { for (int j = 0; j < p; j++) printf("%d ", comb[j]); printf("\n"); } */
       if (i == p - 1) c++;
       else            { comb[++i] = comb[i - 1]; }
    } else i--; }
  printf("%d!%d == %d combination(s) in %15.3f second(s)\n ", p, n, c, clock()/1000.0);
}

使用cmd.exe (windows)测试:

Microsoft Windows XP [Version 5.1.2600]
(C) Copyright 1985-2001 Microsoft Corp.

c:\Program Files\lcc\projects>combination
16!32 == 601080390 combination(s) in          5.781 second(s)

c:\Program Files\lcc\projects>

祝你有愉快的一天。

下面是我的Scala解决方案:

def combinations[A](s: List[A], k: Int): List[List[A]] = 
  if (k > s.length) Nil
  else if (k == 1) s.map(List(_))
  else combinations(s.tail, k - 1).map(s.head :: _) ::: combinations(s.tail, k)

在Python中，利用递归的优势和所有事情都是通过引用完成的事实。对于非常大的集合，这将占用大量内存，但其优点是初始集合可以是一个复杂的对象。它只会找到唯一的组合。

import copy

def find_combinations( length, set, combinations = None, candidate = None ):
    # recursive function to calculate all unique combinations of unique values
    # from [set], given combinations of [length].  The result is populated
    # into the 'combinations' list.
    #
    if combinations == None:
        combinations = []
    if candidate == None:
        candidate = []

    for item in set:
        if item in candidate:
            # this item already appears in the current combination somewhere.
            # skip it
            continue

        attempt = copy.deepcopy(candidate)
        attempt.append(item)
        # sorting the subset is what gives us completely unique combinations,
        # so that [1, 2, 3] and [1, 3, 2] will be treated as equals
        attempt.sort()

        if len(attempt) < length:
            # the current attempt at finding a new combination is still too
            # short, so add another item to the end of the set
            # yay recursion!
            find_combinations( length, set, combinations, attempt )
        else:
            # the current combination attempt is the right length.  If it
            # already appears in the list of found combinations then we'll
            # skip it.
            if attempt in combinations:
                continue
            else:
                # otherwise, we append it to the list of found combinations
                # and move on.
                combinations.append(attempt)
                continue
    return len(combinations)

你可以这样使用它。传递'result'是可选的，所以你可以用它来获取可能组合的数量…尽管这样做效率很低(最好通过计算来完成)。

size = 3
set = [1, 2, 3, 4, 5]
result = []

num = find_combinations( size, set, result ) 
print "size %d results in %d sets" % (size, num)
print "result: %s" % (result,)

您应该从测试数据中得到以下输出:

size 3 results in 10 sets
result: [[1, 2, 3], [1, 2, 4], [1, 2, 5], [1, 3, 4], [1, 3, 5], [1, 4, 5], [2, 3, 4], [2, 3, 5], [2, 4, 5], [3, 4, 5]]

如果你的集合是这样的，它也会工作得很好:

set = [
    [ 'vanilla', 'cupcake' ],
    [ 'chocolate', 'pudding' ],
    [ 'vanilla', 'pudding' ],
    [ 'chocolate', 'cookie' ],
    [ 'mint', 'cookie' ]
]

Here's some simple code that prints all the C(n,m) combinations. It works by initializing and moving a set of array indices that point to next valid combination. The indices are initialized to point to the lowest m indices (lexicographically the smallest combination). Then on, starting with the m-th index, we try to move the indices forward. if an index has reached its limit, we try the previous index (all the way down to index 1). If we can move an index forward, then we reset all greater indices.

m=(rand()%n)+1; // m will vary from 1 to n

for (i=0;i<n;i++) a[i]=i+1;

// we want to print all possible C(n,m) combinations of selecting m objects out of n
printf("Printing C(%d,%d) possible combinations ...\n", n,m);

// This is an adhoc algo that keeps m pointers to the next valid combination
for (i=0;i<m;i++) p[i]=i; // the p[.] contain indices to the a vector whose elements constitute next combination

done=false;
while (!done)
{
    // print combination
    for (i=0;i<m;i++) printf("%2d ", a[p[i]]);
    printf("\n");

    // update combination
    // method: start with p[m-1]. try to increment it. if it is already at the end, then try moving p[m-2] ahead.
    // if this is possible, then reset p[m-1] to 1 more than (the new) p[m-2].
    // if p[m-2] can not also be moved, then try p[m-3]. move that ahead. then reset p[m-2] and p[m-1].
    // repeat all the way down to p[0]. if p[0] can not also be moved, then we have generated all combinations.
    j=m-1;
    i=1;
    move_found=false;
    while ((j>=0) && !move_found)
    {
        if (p[j]<(n-i)) 
        {
            move_found=true;
            p[j]++; // point p[j] to next index
            for (k=j+1;k<m;k++)
            {
                p[k]=p[j]+(k-j);
            }
        }
        else
        {
            j--;
            i++;
        }
    }
    if (!move_found) done=true;
}