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java实现乘地铁方案的最优选择(票价,距离)

这篇文章主要介绍了java实现乘地铁方案的最优选择(票价,距离),文中通过示例代码介绍的非常详细,对大家的学习或者工作具有一定的参考学习价值,需要的朋友可以参考下

初始问题描述:

已知2条地铁线路,其中A为环线,B为东西向线路,线路都是双向的。经过的站点名分别如下,两条线交叉的换乘点用T1、T2表示。编写程序,任意输入两个站点名称,输出乘坐地铁最少需要经过的车站数量(含输入的起点和终点,换乘站点只计算一次)。

地铁线A(环线)经过车站:A1 A2 A3 A4 A5 A6 A7 A8 A9 T1 A10 A11 A12 A13 T2 A14 A15 A16 A17 A18

地铁线B(直线)经过车站:B1 B2 B3 B4 B5 T1 B6 B7 B8 B9 B10 T2 B11 B12 B13 B14 B15

该特定条件下的实现:

package com.patrick.bishi;
 
import java.util.HashSet;
import java.util.LinkedList;
import java.util.Scanner;
import java.util.Set;
 
/**
 * 获取两条地铁线上两点间的最短站点数
 * 
 * @author patrick
 * 
 */
public class SubTrain {
	private static LinkedList subA = new LinkedList();
	private static LinkedList subB = new LinkedList();
 
	public static void main(String[] args) {
		String sa[] = { "A1", "A2", "A3", "A4", "A5", "A6", "A7", "A8", "A9",
				"T1", "A10", "A11", "A12", "A13", "T2", "A14", "A15", "A16",
				"A17", "A18" };
		String sb[] = { "B1", "B2", "B3", "B4", "B5", "T1", "B6", "B7", "B8",
				"B9", "B10", "T2", "B11", "B12", "B13", "B14", "B15" };
		Set plots = new HashSet();
		for (String t : sa) {
			plots.add(t);
			subA.add(t);
		}
		for (String t : sb) {
			plots.add(t);
			subB.add(t);
		}
		Scanner in = new Scanner(System.in);
		String input = in.nextLine();
		String trail[] = input.split("\\s");
		String src = trail[0];
		String dst = trail[1];
		if (!plots.contains(src) || !plots.contains(dst)) {
			System.err.println("no these plot!");
			return;
		}
		int len = getDistance(src, dst);
		System.out.printf("The shortest distance between %s and %s is %d", src,
				dst, len);
	}
 
	// 经过两个换乘站点后的距离
	public static int getDist(String src, String dst) {
		int len = 0;
		int at1t2 = getDistOne("T1", "T2");
		int bt1t2 = subB.indexOf("T2") - subB.indexOf("T1") + 1;
		int a = 0;
		if (src.equals("T1")) {
			a = getDistOne(dst, "T2");
			len = a + bt1t2 - 1;// two part must more 1
		} else if (src.equals("T2")) {
			a = getDistOne(dst, "T1");
			len = a + bt1t2 - 1;
		} else if (dst.equals("T1")) {
			a = getDistOne(src, "T2");
			len = a + at1t2 - 1;
		} else if (dst.equals("T2")) {
			a = getDistOne(src, "T1");
			len = a + at1t2 - 1;
		}
		return len;
	}
 
	// 获得一个链表上的两个元素的最短距离
	private static int getDistOne(String src, String dst) {
		int aPre, aBack, aLen, len, aPos, bPos;
		aPre = aBack = aLen = len = 0;
		aLen = subA.size();
		if ("T1".equals(src) && "T2".equals(dst)) {
			int a = subA.indexOf("T1");
			int b = subA.indexOf("T2");
			int at1t2 = (b - a) > (a + aLen - b) ? (a + aLen - b) : (b - a);
			int bt1t2 = subB.indexOf("T2") - subB.indexOf("T1");
			len = at1t2 > bt1t2 ? bt1t2 : at1t2;
		} else if (subA.contains(src) && subA.contains(dst)) {
			aPos = subA.indexOf(src);
			bPos = subA.indexOf(dst);
			if (aPos > bPos) {
				aBack = aPos - bPos;
				aPre = aLen - aPos + bPos;
				len = aBack > aPre ? aPre : aBack;
			} else {
				aPre = bPos - aPos;
				aBack = aLen - bPos + aPos;
				len = aBack > aPre ? aPre : aBack;
			}
		} else if (subB.contains(src) && subB.contains(dst)) {
			aPos = subB.indexOf(src);
			bPos = subB.indexOf(dst);
			len = aPos > bPos ? (aPos - bPos) : (bPos - aPos);
		} else {
			System.err.println("Wrong!");
		}
		return len + 1;
	}
 
	public static int getDistance(String src, String dst) {
		int aPre, aBack, len, aLen;
		aPre = aBack = len = aLen = 0;
		aLen = subA.size();
		int a = subA.indexOf("T1");
		int b = subA.indexOf("T2");
		int at1t2 = (b - a) > (a + aLen - b) ? (a + aLen - b) : (b - a);
		int bt1t2 = subB.indexOf("T2") - subB.indexOf("T1");
		if ((subA.contains(src) && subA.contains(dst))
				|| (subB.contains(src) && subB.contains(dst))) {
			len = getDistOne(src, dst);
			if (src.equals("T1") || src.equals("T2") || dst.equals("T1")
					|| dst.equals("T2")) {
				int t = getDist(src, dst);
				len = len > t ? t : len;
			}
		} else {
			int at1 = getDist(src, "T1");
			int at2 = getDist(src, "T2");
			int bt1 = getDist(dst, "T1");
			int bt2 = getDist(dst, "T2");
			aPre = at1 + bt1 - 1;
			aBack = at2 + bt2 - 1;
			len = aBack > aPre ? aPre : aBack;
			aPre = at1t2 + at1 + bt2 - 2;
			aBack = bt1t2 + at2 + bt1 - 2;
			int tmp = aBack > aPre ? aPre : aBack;
			len = len > tmp ? tmp : len;
		}
		return len;
	}
}

通用乘地铁方案的实现(最短距离利用Dijkstra算法):
package com.patrick.bishi;
 
import java.util.ArrayList;
import java.util.List;
import java.util.Scanner;
 
/**
 * 地铁中任意两点的最有路径
 * 
 * @author patrick
 * 
 */
public class SubTrainMap {
	protected int[][] subTrainMatrix; // 图的邻接矩阵,用二维数组表示
	private static final int MAX_WEIGHT = 99; // 设置最大权值,设置成常量
	private int[] dist;
	private List vertex;// 按顺序保存顶点s
	private List edges;
 
	public int[][] getSubTrainMatrix() {
		return subTrainMatrix;
	}
 
	public void setVertex(List vertices) {
		this.vertex = vertices;
	}
 
	public List getVertex() {
		return vertex;
	}
 
	public List getEdges() {
		return edges;
	}
 
	public int getVertexSize() {
		return this.vertex.size();
	}
 
	public int vertexCount() {
		return subTrainMatrix.length;
	}
 
	@Override
	public String toString() {
		String str = "邻接矩阵:\n";
		int n = subTrainMatrix.length;
		for (int i = 0; i ();
		this.subTrainMatrix = new int[size][size];
		this.dist = new int[size];
		for (int i = 0; i  vertices) {
		this.vertex = vertices;
		int size = getVertexSize();
		this.subTrainMatrix = new int[size][size];
		this.dist = new int[size];
		for (int i = 0; i 边的权值
 
	public void insertEdge(T start, T stop, int weight) { // 插入一条边
		int n = subTrainMatrix.length;
		int i = getPosInvertex(start);
		int j = getPosInvertex(stop);
		if (i >= 0 && i = 0 && j = 0 && i = 0 && j  vertices = new ArrayList();
		vertices.add("A");
		vertices.add("B");
		vertices.add("C");
		vertices.add("D");
		vertices.add("E");
 
		graph = new SubTrainMap(vertices);
 
		graph.addEdge("A", "B", 5);
		graph.addEdge("A", "D", 2);
		graph.addEdge("B", "C", 7);
		graph.addEdge("B", "D", 6);
		graph.addEdge("C", "D", 8);
		graph.addEdge("C", "E", 3);
		graph.addEdge("D", "E", 9);
 
	}
 
	private static SubTrainMap graph;
 
	/** 打印顶点之间的距离 */
	public void printL(int[][] a) {
		for (int i = 0; i  vertices = new ArrayList();
		for (String t : sa) {
			if (!vertices.contains(t)) {
				vertices.add(t);
			}
		}
		for (String t : sb) {
			if (!vertices.contains(t)) {
				vertices.add(t);
			}
		}
		graph = new SubTrainMap(vertices);
		for (int i = 0; i  " + stop + " 经过的站点数为: " + len);
	}
 
	public int find(T start, T stop) {
		int startPos = getPosInvertex(start);
		int stopPos = getPosInvertex(stop);
		if (startPos <0 || startPos > getVertexSize())
			return MAX_WEIGHT;
		String[] path = dijkstra(startPos);
		System.out.println("从" + start + "出发到" + stop + "的最短路径为:"
				+ path[stopPos]);
		return dist[stopPos];
	}
 
	// 单元最短路径问题的Dijkstra算法
	private String[] dijkstra(int vertex) {
		int n = dist.length - 1;
		String[] path = new String[n + 1]; // 存放从start到其他各点的最短路径的字符串表示
		for (int i = 0; i <= n; i++)
			path[i] = new String(this.vertex.get(vertex) + "-->"
					+ this.vertex.get(i));
 
		boolean[] visited = new boolean[n + 1];
		// 初始化
		for (int i = 0; i <= n; i++) {
			dist[i] = subTrainMatrix[vertex][i];// 到各个顶点的距离,根据顶点v的数组初始化
			visited[i] = false;// 初始化访问过的节点,当然都没有访问过
		}
 
		dist[vertex] = 0;
		visited[vertex] = true;
 
		for (int i = 1; i <= n; i++) {// 将所有的节点都访问到
			int temp = MAX_WEIGHT;
			int visiting = vertex;
			for (int j = 0; j <= n; j++) {
				if ((!visited[j]) && (dist[j] " + this.vertex.get(j);
				}
			}// update all new distance
 
		}// visite all nodes
			// for (int i = 0; i <= n; i++)
		// System.out.println("从" + vertex + "出发到" + i + "的最短路径为:" + path[i]);
		// System.out.println("=====================================");
		return path;
	}
 
	/**
	 * 图的边
	 * 
	 * @author patrick
	 * 
	 */
	class Edge {
		private T start, dest;
		private int weight;
 
		public Edge() {
		}
 
		public Edge(T start, T dest, int weight) {
			this.start = start;
			this.dest = dest;
			this.weight = weight;
		}
 
		public String toString() {
			return "(" + start + "," + dest + "," + weight + ")";
		}
 
	}
 
}

图中各边的权可以是距离也可以是票价,初始化的方案决定实现的目标。最短路径计算也可以用Floyd算法实现。欢迎其他人讨论和提供实现。

以上就是本文的全部内容,希望对大家的学习有所帮助,也希望大家多多支持。


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