Kappa Values for BPSO

src/algorithm/objectiveFunction/ObjectiveFunctionByCarlos.java

@@ -15,10 +15,12 @@ public class ObjectiveFunctionByCarlos {
 	static double w_eb = .3, w_state = .3, w_pro = .2, w_perf = .1, w_holon=.1;
 	
 	//kappas for squashing function
-//	static double k_eb = 1500000.f, k_state = 40000, k_pro = 6000, k_perf = 15000, k_holon= 400000;
-	static double k_eb = 750000.f, k_state = 20000, k_pro = 3000, k_perf = 15000, k_holon= 200000;
+//	
+	static double k_eb = 1050000.f, k_state = 10000, k_pro = 2000, k_perf = 11000, k_holon= 150000;
+//  oversupplied
+//	static double k_eb = 750000.f, k_state = 20000, k_pro = 3000, k_perf = 15000, k_holon= 200000;
 	
-//	old values
+//	old values undersupplied 
 //	static double k_eb = 1000000.f, k_state = 15000, k_pro = 2100, k_perf = 12000, k_holon= 200000;
 	
 	//theta for f_pro
@@ -92,10 +94,6 @@ public class ObjectiveFunctionByCarlos {
 	static public float getFitnessValueForState(DecoratedState state) {
 		
 		//Calculate f_eb the penalty for unbalenced energy in the network
-		
-		//TODO: Hier sollte zwischen den Netzwerken verschiedenen Holons unterschieden werden dies ist in den Formeln nicht wiedergegeben
-		// Kann somit schlechte und gute Netzwerke ausgleichen
-		// Implementierung ist wie im paper.
 		double f_eb = 0;
 		//sum over all objects
 		for(DecoratedNetwork net : state.getNetworkList()) {
@@ -181,8 +179,8 @@ public class ObjectiveFunctionByCarlos {
 		double q5 = squash(f_holon, k_holon);
 //		System.out.print( "f_eb=" + q1);
 //		System.out.print( " f_state=" + q2);
-//		System.out.print( " f_pro=" + q3);
-//		System.out.print( " f_perf=" + q4);
+//		System.out.println( " f_pro=" + q3);
+//		System.out.println( " f_perf=" + q4);
 //		System.out.println( " f_holon=" + q5);
 //		
 		return (float) (w_eb * q1 + w_state * q2 + w_pro * q3 + w_perf * q4 + w_holon * q5);