只是想建议使用IComparer<T>和List.Sort()的变体:

public class RandomIntComparer : IComparer<int>
{
    private readonly Random _random = new Random();
    
    public int Compare(int x, int y)
    {
        return _random.Next(-1, 2);
    }
}

用法:

list.Sort(new RandomIntComparer());

这里是Fisher-Yates shuffle的实现，允许指定返回的元素数量;因此，在获取所需数量的元素之前，没有必要首先对整个集合进行排序。

交换元素的顺序与默认值相反;从第一个元素到最后一个元素，因此检索集合的一个子集与洗牌整个集合产生相同的(部分)序列:

collection.TakeRandom(5).SequenceEqual(collection.Shuffle().Take(5)); // true

该算法基于Durstenfeld在维基百科上的(现代)Fisher-Yates shuffle。

public static IList<T> TakeRandom<T>(this IEnumerable<T> collection, int count, Random random) => shuffle(collection, count, random);
public static IList<T> Shuffle<T>(this IEnumerable<T> collection, Random random) => shuffle(collection, null, random);
private static IList<T> shuffle<T>(IEnumerable<T> collection, int? take, Random random)
{
    var a = collection.ToArray();
    var n = a.Length;
    if (take <= 0 || take > n) throw new ArgumentException("Invalid number of elements to return.");
    var end = take ?? n;
    for (int i = 0; i < end; i++)
    {
        var j = random.Next(i, n);
        (a[i], a[j]) = (a[j], a[i]);
    }

    if (take.HasValue) return new ArraySegment<T>(a, 0, take.Value);
    return a;
}

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。

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());
}

 public Deck(IEnumerable<Card> initialCards) 
    {
    cards = new List<Card>(initialCards);
    public void Shuffle() 
     }
    {
        List<Card> NewCards = new List<Card>();
        while (cards.Count > 0) 
        {
            int CardToMove = random.Next(cards.Count);
            NewCards.Add(cards[CardToMove]);
            cards.RemoveAt(CardToMove);
        }
        cards = NewCards;
    }

public IEnumerable<string> GetCardNames() 

{
    string[] CardNames = new string[cards.Count];
    for (int i = 0; i < cards.Count; i++)
    CardNames[i] = cards[i].Name;
    return CardNames;
}

Deck deck1;
Deck deck2;
Random random = new Random();

public Form1() 
{

InitializeComponent();
ResetDeck(1);
ResetDeck(2);
RedrawDeck(1);
 RedrawDeck(2);

}



 private void ResetDeck(int deckNumber) 
    {
    if (deckNumber == 1) 
{
      int numberOfCards = random.Next(1, 11);
      deck1 = new Deck(new Card[] { });
      for (int i = 0; i < numberOfCards; i++)
           deck1.Add(new Card((Suits)random.Next(4),(Values)random.Next(1, 14)));
       deck1.Sort();
}


   else
    deck2 = new Deck();
 }

private void reset1_Click(object sender, EventArgs e) {
ResetDeck(1);
RedrawDeck(1);

}

private void shuffle1_Click(object sender, EventArgs e) 
{
    deck1.Shuffle();
    RedrawDeck(1);

}

private void moveToDeck1_Click(object sender, EventArgs e) 
{

    if (listBox2.SelectedIndex >= 0)
    if (deck2.Count > 0) {
    deck1.Add(deck2.Deal(listBox2.SelectedIndex));

}

    RedrawDeck(1);
    RedrawDeck(2);

}