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;
}

通过使用元组进行交换，可以使Fisher-Yates shuffle更加简洁和富有表现力。

private static readonly Random random = new Random();

public static void Shuffle<T>(this IList<T> list)
{
    int n = list.Count;
    while (n > 1)
    {
        n--;
        int k = random.Next(n + 1);
        (list[k], list[n]) = (list[n], list[k]);
    }
}

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!

IEnumerable扩展方法:

public static IEnumerable<T> Randomize<T>(this IEnumerable<T> source)
{
    Random rnd = new Random();
    return source.OrderBy<T, int>((item) => rnd.Next());
}

我通常使用:

var list = new List<T> ();
fillList (list);
var randomizedList = new List<T> ();
var rnd = new Random ();
while (list.Count != 0)
{
    var index = rnd.Next (0, list.Count);
    randomizedList.Add (list [index]);
    list.RemoveAt (index);
}

解决这类问题的一个非常简单的方法是在列表中使用一些随机的元素交换。

在伪代码中是这样的:

do 
    r1 = randomPositionInList()
    r2 = randomPositionInList()
    swap elements at index r1 and index r2 
for a certain number of times