import java.lang.Math; import java.util.Comparator; import java.util.Arrays; public class Main{ public static void main(String[] args){ int NC=30;//number of cities int NT=100;//number of travellers City[] cities=new City[NC]; for(int i=0;i0.5){ Traveller temp=mom; mom=dad; dad=temp; } pop[i]=getBaby(mom,dad); } } //loop end System.out.println("\nbest distance found after 200 generations of 100 travellers: "+pop[0].distance); pop[0].printTraj(); } private static void calcDistances(City[] cities,Traveller[] travellers){ for(Traveller t:travellers){ double dist=0; int x=cities[t.trajectory[0]].x; int y=cities[t.trajectory[0]].y; for(int i=0;i=crossPoint&&i-1){ bPoint++; } babyTraj[i]=b.trajectory[bPoint]; bPoint++; } } Traveller baby=new Traveller(); while(Math.random()<0.3){ //mutation random swap int indexA=(int)(Math.random()*NC); int indexB=(int)(Math.random()*NC); int temp=babyTraj[indexA]; babyTraj[indexA]=babyTraj[indexB]; babyTraj[indexB]=temp; } baby.trajectory=babyTraj; return baby; } } public class City{ public City(){ this.x=(int)(Math.random()*1000); this.y=(int)(Math.random()*1000); } int x,y; } public class Traveller{ public Traveller(){ for(int i=0;i0;i--){ int j=(int)(Math.random()*(i+1)); var temp = trajectory[i]; trajectory[i] = trajectory[j]; trajectory[j] = temp; } } public void printTraj(){ System.out.println(); for(int t:trajectory) System.out.print(t+" "); System.out.println(); } int NC=30;//number of cities int[] trajectory=new int[NC]; int distance; } class SortbyDistance implements Comparator{ public int compare(Traveller a, Traveller b) { return a.distance-b.distance; } }

travelling salesman - genetic algorithm