深度优先搜索和广度优先搜索(1)
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一、深度优先搜索
二、
在一个3乘3的九宫中有1-8的8个数及一个空格随机摆放在其中的格子里。如下面左图所示。现在要求实现这样的问题:将该九宫调整为如下图右图所示的形式。调整规则是:每次只能将与空格(上,下或左,右)相临的一个数字平移到空格中。试编程实现。
| 2 | 8
-
| 1|
| 7 |
深度优先搜索的路径示意图:
三、广度优先搜索
广度优先搜索路径示意图:
四、航班问题(来自《The Art of Java》)
下面是用深度优先搜索求解的程序:
// Find connections using a depth-first search.import java.util.*;import java.io.*;// Flight information.class FlightInfo { String from; String to; int distance; boolean skip; // used in backtracking FlightInfo(String f, String t, int d) { from = f; to = t; distance = d; skip = false; }}class Depth { final int MAX = 100; // This array holds the flight information. FlightInfo flights[] = new FlightInfo[MAX]; int numFlights = 0; // number of entries in flight array Stack btStack = new Stack(); // backtrack stack public static void main(String args[]) { String to, from; Depth ob = new Depth(); BufferedReader br = new BufferedReader(new InputStreamReader(System.in)); ob.setup(); try { System.out.print("From? "); from = br.readLine(); System.out.print("To? "); to = br.readLine(); ob.isflight(from, to); if(ob.btStack.size() != 0) ob.route(to); } catch (IOException exc) { System.out.println("Error on input."); } } // Initialize the flight database. void setup() { addFlight("New York", "Chicago", 900); addFlight("Chicago", "Denver", 1000); addFlight("New York", "Toronto", 500); addFlight("New York", "Denver", 1800); addFlight("Toronto", "Calgary", 1700); addFlight("Toronto", "Los Angeles", 2500); addFlight("Toronto", "Chicago", 500); addFlight("Denver", "Urbana", 1000); addFlight("Denver", "Houston", 1000); addFlight("Houston", "Los Angeles", 1500); addFlight("Denver", "Los Angeles", 1000); } // Put flights into the database. void addFlight(String from, String to, int dist) { if(numFlights < MAX) { flights[numFlights] = new FlightInfo(from, to, dist); numFlights++; } else System.out.println("Flight database full.\n"); } // Show the route and total distance. void route(String to) { Stack rev = new Stack(); int dist = 0; FlightInfo f; int num = btStack.size(); // Reverse the stack to display route. for(int i=0; i < num; i++) rev.push(btStack.pop()); for(int i=0; i < num; i++) { f = (FlightInfo) rev.pop(); System.out.print(f.from + " to "); dist += f.distance; } System.out.println(to); System.out.println("Distance is " + dist); } int match(String from, String to) { for(int i=numFlights-1; i > -1; i--) { if(flights[i].from.equals(from) && flights[i].to.equals(to) && !flights[i].skip) { flights[i].skip = true; // prevent reuse return flights[i].distance; } } return 0; // not found } // Given from, find any connection. FlightInfo find(String from) { for(int i=0; i < numFlights; i++) { if(flights[i].from.equals(from) && !flights[i].skip) { FlightInfo f = new FlightInfo(flights[i].from, flights[i].to, flights[i].distance); flights[i].skip = true; // prevent reuse return f; } } return null; } // Determine if there is a route between from and to. void isflight(String from, String to) { int dist; FlightInfo f; // See if at destination. dist = match(from, to); if(dist != 0) { btStack.push(new FlightInfo(from, to, dist)); return; } // Try another connection. f = find(from); if(f != null) { btStack.push(new FlightInfo(from, to, f.distance)); isflight(f.to, to); } else if(btStack.size() > 0) { // Backtrack and try another connection. f = (FlightInfo) btStack.pop(); isflight(f.from, f.to); } }}
- 深度优先搜索和广度优先搜索(1)
- 深度优先搜索和广度优先搜索
- 深度优先搜索和广度优先搜索
- 深度优先搜索和广度优先搜索
- 深度优先搜索和广度优先搜索
- 广度优先搜索和深度优先搜索
- 广度优先搜索和深度优先搜索
- 深度优先搜索和广度优先搜索
- 广度优先搜索和深度优先搜索
- 深度优先搜索和广度优先搜索
- 深度优先搜索和广度优先搜索
- 深度优先搜索和广度优先搜索
- 深度优先搜索和广度优先搜索
- 广度优先搜索和深度优先搜索
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