1 files changed, 8 insertions, 20 deletions
diff --git a/src/jcgp/backend/modules/problem/SymbolicRegressionProblem.java b/src/jcgp/backend/modules/problem/SymbolicRegressionProblem.java
index 52df0f2..5468157 100644
--- a/src/jcgp/backend/modules/problem/SymbolicRegressionProblem.java
+++ b/src/jcgp/backend/modules/problem/SymbolicRegressionProblem.java
@@ -1,6 +1,6 @@
 package jcgp.backend.modules.problem;
 
-import jcgp.backend.function.DoubleArithmetic;
+import jcgp.backend.function.SymbolicRegressionFunctions;
 import jcgp.backend.population.Chromosome;
 import jcgp.backend.population.Population;
 import jcgp.backend.resources.Resources;
@@ -16,7 +16,9 @@ public class SymbolicRegressionProblem extends TestCaseProblem<Double> {
 	
 	public SymbolicRegressionProblem(Resources resources) {
 		super(resources);
-		functionSet = new DoubleArithmetic();
+		functionSet = new SymbolicRegressionFunctions();
+		setProblemName("Symbolic regression");
+		setFileExtension(".dat");
 		errorThreshold = new DoubleParameter(0.01, "Error threshold") {
 			@Override
 			public void validate(Number newValue) {
@@ -45,7 +47,7 @@ public class SymbolicRegressionProblem extends TestCaseProblem<Double> {
 				}
 			}
 		};
-		hitsBasedFitness = new BooleanParameter(true, "Hits-based fitness") {
+		hitsBasedFitness = new BooleanParameter(true, "HITS-based fitness") {
 			@Override
 			public void validate(Boolean newValue) {
 				// blank
@@ -55,9 +57,6 @@ public class SymbolicRegressionProblem extends TestCaseProblem<Double> {
 	
 	@Override
 	public void evaluate(Population population, Resources resources) {
-		// set fittest to 0, change it whenever a fitter one is found
-		population.setFittest(0);
-		
 		// for every chromosome in the population
 		for (int i = 0; i < resources.populationSize(); i++) {
 			// assume an initial fitness of 0
@@ -81,18 +80,12 @@ public class SymbolicRegressionProblem extends TestCaseProblem<Double> {
 			}
 			// assign the resulting fitness to the respective individual
 			population.getChromosome(i).setFitness(fitness);
-			if (fitness >= population.getFittest().getFitness()) {
-				population.setFittest(i);
-			}
 		}
+		
+		// sort population
+		population.sortAscending();
 	}
 	
-	
-	@Override
-	public String toString() {
-		return "Symbolic regression";
-	}
-
 	@Override
 	public void addTestCase(String[] inputs, String[] outputs) {
 		Double[] inputCases = new Double[inputs.length];
@@ -116,9 +109,4 @@ public class SymbolicRegressionProblem extends TestCaseProblem<Double> {
 	public Parameter<?>[] getLocalParameters() {
 		return new Parameter[]{maxFitness, errorThreshold, perfectionThreshold, hitsBasedFitness};
 	}
-
-	@Override
-	public String getFileExtension() {
-		return ".dat";
-	}
 }