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：
即在队列两端都可以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。插入时需要比较查找插入的位置，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，从头开始
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，从头开始
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);

}

}