如果您有一个固定的数字(75)，您可以创建一个包含75个元素的数组，然后枚举您的列表，将元素移动到数组中的随机位置。您可以使用Fisher-Yates shuffle生成列表号到数组索引的映射。

如果我们只需要以完全随机的顺序洗牌项目(只是在一个列表中混合项目)，我更喜欢这个简单而有效的代码，按guid排序项目…

var shuffledcards = cards.OrderBy(a => Guid.NewGuid()).ToList();

正如人们在评论中指出的那样，guid不能保证是随机的，所以我们应该使用真正的随机数生成器:

private static Random rng = new Random();
...
var shuffledcards = cards.OrderBy(a => rng.Next()).ToList();

您可以使用这个简单的扩展方法来实现这一点

public static class IEnumerableExtensions
{

    public static IEnumerable<t> Randomize<t>(this IEnumerable<t> target)
    {
        Random r = new Random();

        return target.OrderBy(x=>(r.Next()));
    }        
}

你可以通过下面的步骤来使用它

// use this on any collection that implements IEnumerable!
// List, Array, HashSet, Collection, etc

List<string> myList = new List<string> { "hello", "random", "world", "foo", "bar", "bat", "baz" };

foreach (string s in myList.Randomize())
{
    Console.WriteLine(s);
}

这是我最喜欢的shuffle方法，当不需要修改原始的时候。它是Fisher-Yates“由内到外”算法的变体，适用于任何可枚举序列(源的长度不需要从一开始就知道)。

public static IList<T> NextList<T>(this Random r, IEnumerable<T> source)
{
  var list = new List<T>();
  foreach (var item in source)
  {
    var i = r.Next(list.Count + 1);
    if (i == list.Count)
    {
      list.Add(item);
    }
    else
    {
      var temp = list[i];
      list[i] = item;
      list.Add(temp);
    }
  }
  return list;
}

该算法还可以通过分配一个从0到length - 1的范围来实现，并通过将随机选择的索引与最后一个索引交换来随机耗尽索引，直到所有索引都被选中一次。上面的代码完成了完全相同的事情，但没有额外的分配。非常简洁。

With regards to the Random class it's a general purpose number generator (and If I was running a lottery I'd consider using something different). It also relies on a time based seed value by default. A small alleviation of the problem is to seed the Random class with the RNGCryptoServiceProvider or you could use the RNGCryptoServiceProvider in a method similar to this (see below) to generate uniformly chosen random double floating point values but running a lottery pretty much requires understanding randomness and the nature of the randomness source.

var bytes = new byte[8];
_secureRng.GetBytes(bytes);
var v = BitConverter.ToUInt64(bytes, 0);
return (double)v / ((double)ulong.MaxValue + 1);

生成随机双精度(仅在0和1之间)的目的是用于扩展到整数解。如果你需要从一个基于随机双x的列表中选择一个东西，它总是0 <= x && x < 1是很简单的。

return list[(int)(x * list.Count)];

享受吧!

I'm bit surprised by all the clunky versions of this simple algorithm here. Fisher-Yates (or Knuth shuffle) is bit tricky but very compact. Why is it tricky? Because your need to pay attention to whether your random number generator r(a,b) returns value where b is inclusive or exclusive. I've also edited Wikipedia description so people don't blindly follow pseudocode there and create hard to detect bugs. For .Net, Random.Next(a,b) returns number exclusive of b so without further ado, here's how it can be implemented in C#/.Net:

public static void Shuffle<T>(this IList<T> list, Random rnd)
{
    for(var i=list.Count; i > 0; i--)
        list.Swap(0, rnd.Next(0, i));
}

public static void Swap<T>(this IList<T> list, int i, int j)
{
    var temp = list[i];
    list[i] = list[j];
    list[j] = temp;
}

试试这段代码。

对已接受答案的简单修改，返回一个新的列表，而不是原地工作，并像许多其他Linq方法一样接受更通用的IEnumerable<T>。

private static Random rng = new Random();

/// <summary>
/// Returns a new list where the elements are randomly shuffled.
/// Based on the Fisher-Yates shuffle, which has O(n) complexity.
/// </summary>
public static IEnumerable<T> Shuffle<T>(this IEnumerable<T> list) {
    var source = list.ToList();
    int n = source.Count;
    var shuffled = new List<T>(n);
    shuffled.AddRange(source);
    while (n > 1) {
        n--;
        int k = rng.Next(n + 1);
        T value = shuffled[k];
        shuffled[k] = shuffled[n];
        shuffled[n] = value;
    }
    return shuffled;
}