Importing release version 322 from old repos
This commit is contained in:
Marcel Kronfeld
210
src/javaeva/server/modules/EPParameters.java
Normal file
210
src/javaeva/server/modules/EPParameters.java
Normal file
@@ -0,0 +1,210 @@
|
||||
package javaeva.server.modules;
|
||||
|
||||
import javaeva.server.go.InterfaceGOParameters;
|
||||
import javaeva.server.go.InterfacePopulationChangedEventListener;
|
||||
import javaeva.server.go.TerminatorInterface;
|
||||
import javaeva.server.go.operators.selection.InterfaceSelection;
|
||||
import javaeva.server.go.operators.terminators.EvaluationTerminator;
|
||||
import javaeva.server.go.populations.Population;
|
||||
import javaeva.server.go.problems.F1Problem;
|
||||
import javaeva.server.go.problems.InterfaceOptimizationProblem;
|
||||
import javaeva.server.go.strategies.EvolutionaryProgramming;
|
||||
import javaeva.server.go.strategies.InterfaceOptimizer;
|
||||
import javaeva.tools.Serializer;
|
||||
|
||||
import java.io.Serializable;
|
||||
|
||||
/** The class gives access to all EP parameters for the JavaEvA
|
||||
* top level GUI.
|
||||
* Created by IntelliJ IDEA.
|
||||
* User: streiche
|
||||
* Date: 27.10.2004
|
||||
* Time: 13:49:09
|
||||
* To change this template use File | Settings | File Templates.
|
||||
*/
|
||||
public class EPParameters implements InterfaceGOParameters, Serializable {
|
||||
|
||||
public static boolean TRACE = false;
|
||||
private String m_Name ="not defined";
|
||||
private long m_Seed = (long)100.0;
|
||||
|
||||
// Opt. Algorithms and Parameters
|
||||
private InterfaceOptimizer m_Optimizer = new EvolutionaryProgramming();
|
||||
private InterfaceOptimizationProblem m_Problem = new F1Problem();
|
||||
//private int m_FunctionCalls = 1000;
|
||||
private TerminatorInterface m_Terminator = new EvaluationTerminator();
|
||||
private String m_OutputFileName = "none";
|
||||
transient private InterfacePopulationChangedEventListener m_Listener;
|
||||
|
||||
/**
|
||||
*
|
||||
*/
|
||||
public static EPParameters getInstance() {
|
||||
if (TRACE) System.out.println("EPParameters getInstance 1");
|
||||
EPParameters Instance = (EPParameters) Serializer.loadObject("EPParameters.ser");
|
||||
if (TRACE) System.out.println("EPParameters getInstance 2");
|
||||
if (Instance == null) Instance = new EPParameters();
|
||||
return Instance;
|
||||
}
|
||||
|
||||
/**
|
||||
*
|
||||
*/
|
||||
public void saveInstance() {
|
||||
Serializer.storeObject("EPParameters.ser",this);
|
||||
}
|
||||
/**
|
||||
*
|
||||
*/
|
||||
public EPParameters() {
|
||||
if (TRACE) System.out.println("EPParameters Constructor start");
|
||||
this.m_Name="Optimization parameters";
|
||||
this.m_Optimizer = new EvolutionaryProgramming();
|
||||
this.m_Problem = new F1Problem();
|
||||
//this.m_FunctionCalls = 1000;
|
||||
((EvaluationTerminator)this.m_Terminator).setFitnessCalls(1000);
|
||||
this.m_Optimizer.SetProblem(this.m_Problem);
|
||||
if (TRACE) System.out.println("EPParameters Constructor end");
|
||||
}
|
||||
|
||||
/**
|
||||
*
|
||||
*/
|
||||
private EPParameters(EPParameters Source) {
|
||||
this.m_Name = Source.m_Name;
|
||||
this.m_Optimizer = Source.m_Optimizer;
|
||||
this.m_Problem = Source.m_Problem;
|
||||
this.m_Terminator = Source.m_Terminator;
|
||||
//this.m_FunctionCalls = Source.m_FunctionCalls;
|
||||
this.m_Optimizer.SetProblem(this.m_Problem);
|
||||
this.m_Seed = Source.m_Seed;
|
||||
}
|
||||
/**
|
||||
*
|
||||
*/
|
||||
public String getName() {
|
||||
return m_Name;
|
||||
}
|
||||
/**
|
||||
*
|
||||
*/
|
||||
public Object clone() {
|
||||
return new EPParameters(this);
|
||||
}
|
||||
|
||||
/** This method allows you to add the LectureGUI as listener to the Optimizer
|
||||
* @param ea
|
||||
*/
|
||||
public void addPopulationChangedEventListener(InterfacePopulationChangedEventListener ea) {
|
||||
this.m_Listener = ea;
|
||||
if (this.m_Optimizer != null) this.m_Optimizer.addPopulationChangedEventListener(this.m_Listener);
|
||||
}
|
||||
|
||||
/**
|
||||
*
|
||||
*/
|
||||
public String toString() {
|
||||
String ret = "\r\nEP-Parameter:"+this.m_Problem.getStringRepresentationForProblem(this.m_Optimizer)+"\n"+this.m_Optimizer.getStringRepresentation();
|
||||
return ret;
|
||||
}
|
||||
|
||||
/** This method returns a global info string
|
||||
* @return description
|
||||
*/
|
||||
public String globalInfo() {
|
||||
return "This is a Evolutionary Programming optimization method, please limit EP to mutation operators only.";
|
||||
}
|
||||
|
||||
/** This methods allow you to set and get the Seed for the Random Number Generator.
|
||||
* @param x Long seed.
|
||||
*/
|
||||
public void setSeed(long x) {
|
||||
m_Seed = x;
|
||||
}
|
||||
public long getSeed() {
|
||||
return m_Seed;
|
||||
}
|
||||
public String seedTipText() {
|
||||
return "Random number seed.";
|
||||
}
|
||||
|
||||
/** This method allows you to set the current optimizing algorithm
|
||||
* @param optimizer The new optimizing algorithm
|
||||
*/
|
||||
public void setOptimizer(InterfaceOptimizer optimizer) {
|
||||
// i'm a Monte Carlo Search Algorithm
|
||||
// *pff* i'll ignore that!
|
||||
}
|
||||
public InterfaceOptimizer getOptimizer() {
|
||||
return this.m_Optimizer;
|
||||
}
|
||||
|
||||
/** This method allows you to choose a termination criteria for the
|
||||
* evolutionary algorithm.
|
||||
* @param term The new terminator
|
||||
*/
|
||||
public void setTerminator(TerminatorInterface term) {
|
||||
this.m_Terminator = term;
|
||||
}
|
||||
public TerminatorInterface getTerminator() {
|
||||
return this.m_Terminator;
|
||||
}
|
||||
public String terminatorTipText() {
|
||||
return "Choose a termination criterion.";
|
||||
}
|
||||
|
||||
/** This method will set the problem that is to be optimized
|
||||
* @param problem
|
||||
*/
|
||||
public void setProblem (InterfaceOptimizationProblem problem) {
|
||||
this.m_Problem = problem;
|
||||
this.m_Optimizer.SetProblem(this.m_Problem);
|
||||
}
|
||||
public InterfaceOptimizationProblem getProblem() {
|
||||
return this.m_Problem;
|
||||
}
|
||||
public String problemTipText() {
|
||||
return "Choose the problem that is to optimize and the EA individual parameters.";
|
||||
}
|
||||
|
||||
/** This method will set the output filename
|
||||
* @param name
|
||||
*/
|
||||
public void setOutputFileName (String name) {
|
||||
this.m_OutputFileName = name;
|
||||
}
|
||||
public String getOutputFileName () {
|
||||
return this.m_OutputFileName;
|
||||
}
|
||||
public String outputFileNameTipText() {
|
||||
return "Set the name for the output file, if 'none' no output file will be created.";
|
||||
}
|
||||
|
||||
/** Assuming that all optimizer will store thier data in a population
|
||||
* we will allow acess to this population to query to current state
|
||||
* of the optimizer.
|
||||
* @return The population of current solutions to a given problem.
|
||||
*/
|
||||
public Population getPopulation() {
|
||||
return ((EvolutionaryProgramming)this.m_Optimizer).getPopulation();
|
||||
}
|
||||
public void setPopulation(Population pop){
|
||||
((EvolutionaryProgramming)this.m_Optimizer).setPopulation(pop);
|
||||
}
|
||||
public String populationTipText() {
|
||||
return "Edit the properties of the population used.";
|
||||
}
|
||||
|
||||
/** Choose the type of environment selection to use.
|
||||
* @param selection
|
||||
*/
|
||||
public void setEnvironmentSelection(InterfaceSelection selection) {
|
||||
((EvolutionaryProgramming)this.m_Optimizer).setEnvironmentSelection(selection);
|
||||
}
|
||||
public InterfaceSelection getEnvironmentSelection() {
|
||||
return ((EvolutionaryProgramming)this.m_Optimizer).getEnvironmentSelection();
|
||||
}
|
||||
public String environmentSelectionTipText() {
|
||||
return "Choose a method for selecting the reduced population.";
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user