Java 模拟队列(一般队列、双端队列、优先级队列)

队列:

先进先出,处理类似排队的问题,先排的。先处理,后排的等前面的处理完了,再处理

对于插入和移除操作的时间复杂度都为O(1)。从后面插入,从前面移除

双端队列:

即在队列两端都能够insert和remove:insertLeft、insertRight。removeLeft、removeRight

含有栈和队列的功能,如去掉insertLeft、removeLeft,那就跟栈一样了。如去掉insertLeft、removeRight。那就跟队列一样了

一般使用频率较低,时间复杂度 O(1)

优先级队列:

内部维护一个按优先级排序的序列。插入时须要比較查找插入的位置,时间复杂度O(N), 删除O(1)

/*
* 队列 先进先出。一个指针指示插入的位置,一个指针指示取出数据项的位置
*/
public class QueueQ<T> {
private int max;
private T[] ary;
private int front; //队头指针 指示取出数据项的位置
private int rear; //队尾指针 指示插入的位置
private int nItems; //实际数据项个数 public QueueQ(int size) {
this.max = size;
ary = (T[]) new Object[max];
front = 0;
rear = -1;
nItems = 0;
}
//插入队尾
public void insert(T t) {
if (rear == max - 1) {//已到实际队尾,从头開始
rear = -1;
}
ary[++rear] = t;
nItems++;
}
//移除队头
public T remove() {
T temp = ary[front++];
if (front == max) {//列队到尾了,从头開始
front = 0;
}
nItems--;
return temp;
}
//查看队头
public T peek() {
return ary[front];
} public boolean isEmpty() {
return nItems == 0;
} public boolean isFull() {
return nItems == max;
} public int size() {
return nItems;
} public static void main(String[] args) {
QueueQ<Integer> queue = new QueueQ<Integer>(3);
for (int i = 0; i < 5; i++) {
queue.insert(i);
System.out.println("size:" + queue.size());
}
for (int i = 0; i < 5; i++) {
Integer peek = queue.peek();
System.out.println("peek:" + peek);
System.out.println("size:" + queue.size());
}
for (int i = 0; i < 5; i++) {
Integer remove = queue.remove();
System.out.println("remove:" + remove);
System.out.println("size:" + queue.size());
} System.out.println("----"); for (int i = 5; i > 0; i--) {
queue.insert(i);
System.out.println("size:" + queue.size());
}
for (int i = 5; i > 0; i--) {
Integer peek = queue.peek();
System.out.println("peek:" + peek);
System.out.println("size:" + queue.size());
}
for (int i = 5; i > 0; i--) {
Integer remove = queue.remove();
System.out.println("remove:" + remove);
System.out.println("size:" + queue.size());
}
} }
/*
* 双端队列<span style="white-space:pre"> </span>两端插入、删除
*/
public class QueueQT<T> {
private LinkedList<T> list; public QueueQT() {
list = new LinkedList<T>();
} // 插入队头
public void insertLeft(T t) {
list.addFirst(t);
} // 插入队尾
public void insertRight(T t) {
list.addLast(t);
} // 移除队头
public T removeLeft() {
return list.removeFirst();
} // 移除队尾
public T removeRight() {
return list.removeLast();
} // 查看队头
public T peekLeft() {
return list.getFirst();
} // 查看队尾
public T peekRight() {
return list.getLast();
} public boolean isEmpty() {
return list.isEmpty();
} public int size() {
return list.size();
} }
/*
* 优先级队列 队列中按优先级排序。是一个有序的队列
*/
public class QueueQP {
private int max;
private int[] ary;
private int nItems; //实际数据项个数 public QueueQP(int size) {
this.max = size;
ary = new int[max];
nItems = 0;
}
//插入队尾
public void insert(int t) {
int j;
if (nItems == 0) {
ary[nItems++] = t;
} else {
for (j = nItems - 1; j >= 0; j--) {
if (t > ary[j]) {
ary[j + 1] = ary[j]; //前一个赋给后一个 小的在后 相当于用了插入排序。给定序列本来就是有序的。所以效率O(N)
} else {
break;
}
}
ary[j + 1] = t;
nItems++;
}
System.out.println(Arrays.toString(ary));
}
//移除队头
public int remove() {
return ary[--nItems]; //移除优先级小的
}
//查看队尾 优先级最低的
public int peekMin() {
return ary[nItems - 1];
} public boolean isEmpty() {
return nItems == 0;
} public boolean isFull() {
return nItems == max;
} public int size() {
return nItems;
} public static void main(String[] args) {
QueueQP queue = new QueueQP(3);
queue.insert(1);
queue.insert(2);
queue.insert(3);
int remove = queue.remove();
System.out.println("remove:" + remove); } }
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