import org.um.feri.ears.algorithms.Algorithm;
import org.um.feri.ears.algorithms.AlgorithmInfo;
import org.um.feri.ears.algorithms.Author;
import org.um.feri.ears.problems.DoubleSolution;
import org.um.feri.ears.problems.StopCriteriaException;
import org.um.feri.ears.problems.Task;

public class RandomWalkAlgorithm extends Algorithm { //needs to me extended 
	private DoubleSolution i; //EARS Individual includes solution vector and its fitness value
	private boolean debug = true;

	public RandomWalkAlgorithm() { 
		super();
		setDebug(debug);  //EARS prints some debug info
		ai = new AlgorithmInfo("","","RWSi+","Random Walk+");  //EARS add algorithm name
		au =  new Author("robi", "N/A"); //EARS author info
	}

	@Override  
	public DoubleSolution execute(Task taskProblem) throws StopCriteriaException{ //EARS main evaluation loop 
		DoubleSolution ii;
		i = taskProblem.getRandomSolution(); //EARS Helper for creating random solution, it takes one evaluation (eval++)
		//user can use its own representation for example double[] and in fase of evaluation calls taskProblem.eval that creates individual
		System.out.println(taskProblem.getNumberOfEvaluations()+" "+i); //prints number of evaluations

		while (!taskProblem.isStopCriteria()) {   //EARS user needs to take care about number of evaluations
			ii = taskProblem.getRandomSolution();
			if (taskProblem.isFirstBetter(ii, i)) { //EARS primary function it takes care if we are searching minimum or maximum, if solution is valit etc.
				i = ii;
				if (debug) System.out.println(taskProblem.getNumberOfEvaluations()+" "+i);
			}
		}
		return i;

	}

	@Override
	public void resetDefaultsBeforNewRun() {
		i=null;
	}
}

import org.um.feri.ears.problems.EnumStopCriteria;
import org.um.feri.ears.problems.StopCriteriaException;
import org.um.feri.ears.problems.Task;
import org.um.feri.ears.problems.unconstrained.Sphere;

public class Main4Run {
	public static void main(String[] args) {
		Task t = new Task(EnumStopCriteria.EVALUATIONS, 5000, 0, 0, 0.0001, new Sphere(5)); //run problem Sphere Dimension 5, 3000 evaluations
		RandomWalkAlgorithm test = new RandomWalkAlgorithm();
		try {
			System.out.println(test.execute(t)); //prints best result afrer 3000 runs
		} catch (StopCriteriaException e) {
			e.printStackTrace();
		}
	}
}

import java.util.ArrayList;
import org.um.feri.ears.algorithms.Algorithm;
import org.um.feri.ears.algorithms.so.abc.ABC;
import org.um.feri.ears.algorithms.so.cro.CRO;
import org.um.feri.ears.algorithms.so.de.DEAlgorithm;
import org.um.feri.ears.algorithms.so.fwa.FWA;
import org.um.feri.ears.algorithms.so.gwo.GWO;
import org.um.feri.ears.algorithms.so.jade.JADE;
import org.um.feri.ears.algorithms.so.random.RandomWalkAlgorithm;
import org.um.feri.ears.algorithms.so.tlbo.TLBOAlgorithm;
import org.um.feri.ears.benchmark.RatingBenchmark;
import org.um.feri.ears.benchmark.RatingRPUOed2;
import org.um.feri.ears.benchmark.RatingRPUOed30;
import org.um.feri.ears.problems.results.BankOfResults;
import org.um.feri.ears.rating.Player;
import org.um.feri.ears.rating.ResultArena;
import org.um.feri.ears.util.Util;

public class SORatingExample {
	
    public static void main(String[] args) {
        Util.rnd.setSeed(System.currentTimeMillis()); //set the seed of the random generator    
        RatingBenchmark.debugPrint = false; //prints one on one results
        //add algorithms to list of players
        ArrayList<Algorithm> players = new ArrayList<Algorithm>();
        players.add(new ABC());
        players.add(new CRO());
        players.add(new GWO());
        players.add(new FWA());
        players.add(new TLBOAlgorithm());
        players.add(new RandomWalkAlgorithm());
        players.add(new DEAlgorithm(DEAlgorithm.JDE_rand_1_bin));
        players.add(new JADE());
        ResultArena ra = new ResultArena(100); 
        RatingRPUOed2 rpuoed2 = new RatingRPUOed2(); //Create benchmark
        RatingRPUOed30 rpuoed30 = new RatingRPUOed30();
        
        rpuoed2.registerAlgorithms(players);
        rpuoed30.registerAlgorithms(players);
        
        //set initial rating data for each participating player
        for (Algorithm al:players) {
            ra.addPlayer(al, al.getID(), 1500, 350, 0.06,0,0,0); //init rating 1500
        }
        BankOfResults ba = new BankOfResults();
        
        //rpuoed2.run(ra, ba, 10);
        rpuoed30.run(ra, ba, 10); //start the tournament
        
        //display the leaderboard
        ArrayList<Player> list = ra.getPlayers();
        for (Player p: list) System.out.println(p);
    }
}