import java.util.ArrayList;
import java.util.Random;
public class shuffle {
    public static void main(String[] args) {
        int a[] =  {1,2,3,4,5,6,7,8,9};
         ArrayList b = new ArrayList();
       int i=0,q=0;
       Random rand = new Random();

       while(a.length!=b.size())
       {
           int l = rand.nextInt(a.length);
//this is one option to that but has a flaw on 0
//           if(a[l] !=0)
//           {
//                b.add(a[l]);
//               a[l]=0;
//               
//           }
//           
// this works for every no. 
                if(!(b.contains(a[l])))
                {
                    b.add(a[l]);
                }



       }

//        for (int j = 0; j <b.size(); j++) {
//            System.out.println(b.get(j));
//            
//        }
System.out.println(b);
    }

}

看看Collections类，特别是shuffle(…)。

Groovy的一个简单解决方案:

solutionArray.sort{ new Random().nextInt() }

这将对数组列表中的所有元素进行随机排序，存档所有元素洗牌的预期结果。

下面是数组的泛型版本:

import java.util.Random;

public class Shuffle<T> {

    private final Random rnd;

    public Shuffle() {
        rnd = new Random();
    }

    /**
     * Fisher–Yates shuffle.
     */
    public void shuffle(T[] ar) {
        for (int i = ar.length - 1; i > 0; i--) {
            int index = rnd.nextInt(i + 1);
            T a = ar[index];
            ar[index] = ar[i];
            ar[i] = a;
        }
    }
}

考虑到ArrayList基本上只是一个数组，使用ArrayList而不是显式数组并使用Collections.shuffle()可能是明智的。但是，性能测试并没有显示上述方法与Collections.sort()之间有任何显著差异:

Shuffe<Integer>.shuffle(...) performance: 576084 shuffles per second
Collections.shuffle(ArrayList<Integer>) performance: 629400 shuffles per second
MathArrays.shuffle(int[]) performance: 53062 shuffles per second

Apache Commons实现MathArrays。Shuffle限制为int[]，性能损失可能是由于使用了随机数生成器。

这是knuth shuffle算法。

public class Knuth { 

    // this class should not be instantiated
    private Knuth() { }

    /**
     * Rearranges an array of objects in uniformly random order
     * (under the assumption that <tt>Math.random()</tt> generates independent
     * and uniformly distributed numbers between 0 and 1).
     * @param a the array to be shuffled
     */
    public static void shuffle(Object[] a) {
        int n = a.length;
        for (int i = 0; i < n; i++) {
            // choose index uniformly in [i, n-1]
            int r = i + (int) (Math.random() * (n - i));
            Object swap = a[r];
            a[r] = a[i];
            a[i] = swap;
        }
    }

    /**
     * Reads in a sequence of strings from standard input, shuffles
     * them, and prints out the results.
     */
    public static void main(String[] args) {

        // read in the data
        String[] a = StdIn.readAllStrings();

        // shuffle the array
        Knuth.shuffle(a);

        // print results.
        for (int i = 0; i < a.length; i++)
            StdOut.println(a[i]);
    }
}

使用Guava的int . aslist()就像这样简单:

Collections.shuffle(Ints.asList(array));