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);
		
	}
	
}