Find optimal solution using least-cost : Algorithms « Collections Data Structure « Java

Home
Java
1.2D Graphics GUI
2.3D
3.Advanced Graphics
4.Ant
5.Apache Common
6.Chart
7.Class
8.Collections Data Structure
9.Data Type
10.Database SQL JDBC
11.Design Pattern
12.Development Class
13.EJB3
14.Email
15.Event
16.File Input Output
17.Game
18.Generics
19.GWT
20.Hibernate
21.I18N
22.J2EE
23.J2ME
24.JavaFX
25.JDK 6
26.JDK 7
27.JNDI LDAP
28.JPA
29.JSP
30.JSTL
31.Language Basics
32.Network Protocol
33.PDF RTF
34.Reflection
35.Regular Expressions
36.Scripting
37.Security
38.Servlets
39.Spring
40.Swing Components
41.Swing JFC
42.SWT JFace Eclipse
43.Threads
44.Tiny Application
45.Velocity
46.Web Services SOA
47.XML
Java » Collections Data Structure » Algorithms 




Find optimal solution using least-cost
 
/*
 * Chapter 10 - AI-Based Problem Solving The Art of Java by Herbert Schildt and
 * James Holmes McGraw-Hill/Osborne ? 2003
 */

import java.io.BufferedReader;
import java.io.IOException;
import java.io.InputStreamReader;
import java.util.Stack;

// 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;
  }
}

public class Optimal {
  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

  Stack optimal; // holds optimal solution

  int minDist = 10000;

  public static void main(String args[]) {
    String to, from;
    Optimal ob = new Optimal();
    BufferedReader br = new BufferedReader(new InputStreamReader(System.in));
    boolean done = false;
    FlightInfo f;

    ob.setup();

    try {
      System.out.print("From? ");
      from = br.readLine();
      System.out.print("To? ");
      to = br.readLine();
      do {
        ob.isflight(from, to);

        if (ob.btStack.size() == 0)
          done = true;
        else {
          ob.route(to);
          ob.btStack = new Stack();
        }
      while (!done);

      // Display optimal solution.
      if (ob.optimal != null) {
        System.out.println("Optimal solution is: ");

        int num = ob.optimal.size();
        for (int i = 0; i < num; i++) {
          f = (FlightInfoob.optimal.pop();
          System.out.print(f.from " to ");
        }

        System.out.println(to);
        System.out.println("Distance is " + ob.minDist);
      }
    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[numFlightsnew FlightInfo(from, to, dist);

      numFlights++;
    else
      System.out.println("Flight database full.\n");
  }

  // Save shortest route.
  void route(String to) {
    int dist = 0;
    FlightInfo f;
    int num = btStack.size();
    Stack optTemp = new Stack();

    for (int i = 0; i < num; i++) {
      f = (FlightInfobtStack.pop();
      optTemp.push(f)// save route
      dist += f.distance;
    }

    // If shorter, keep this route
    if (minDist > dist) {
      optimal = optTemp;
      minDist = dist;
    }
  }

  /*
   * If there is a flight between from and to, return the distance of flight;
   * otherwise, return 0.
   */
  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 using least-cost.
  FlightInfo find(String from) {
    int pos = -1;
    int dist = 10000// longer than longest route

    for (int i = 0; i < numFlights; i++) {
      if (flights[i].from.equals(from&& !flights[i].skip) {
        // Use the shortest flight.
        if (flights[i].distance < dist) {
          pos = i;
          dist = flights[i].distance;
        }
      }
    }

    if (pos != -1) {
      flights[pos].skip = true// prevent reuse
      FlightInfo f = new FlightInfo(flights[pos].from, flights[pos].to,
          flights[pos].distance);
      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 = (FlightInfobtStack.pop();
      isflight(f.from, f.to);
    }
  }
}

           
         
  














Related examples in the same category
1.AnagramsAnagrams
2.Hanoi puzzleHanoi puzzle
3.FibonacciFibonacci
4.Sieve Sieve
5.Find connections using a depth-first searchFind connections using a depth-first search
6.Find connections using hill climbing.
7.Find the lost keysFind the lost keys
8.Compute the area of a triangle using Heron's FormulaCompute the area of a triangle using Heron's Formula
9.Compute prime numbers
10.Print a table of fahrenheit and celsius temperatures 1
11.Print a table of fahrenheit and celsius temperatures 2
12.Print a table of Fahrenheit and Celsius temperatures 3Print a table of Fahrenheit and Celsius temperatures 3
13.Soundex - the Soundex Algorithm, as described by KnuthSoundex - the Soundex Algorithm, as described by Knuth
14.A programmable Finite State Machine implementation.
15.An extendable Graph datastructure.
16.Utilities for flop (floating-point operation) counting.
17.LU Decomposition
18.Reverse Polish Notation
19.Permutator test
20.implements the LZF lossless data compression algorithm
21.Linear Interpolation
22.Utility class for generating the k-subsets of the numbers 0 to n
23.VersionVersion
java2s.com  | Contact Us | Privacy Policy
Copyright 2009 - 12 Demo Source and Support. All rights reserved.
All other trademarks are property of their respective owners.