Examples of ec.multiobjective.MultiObjectiveFitness

ec.multiobjective.MultiObjectiveFitness

MultiObjectiveFitness is a subclass of Fitness which implements basic multi-objective mechanisms suitable for being used with a variety of multi-objective selection mechanisms, including ones using pareto-optimality.

The object contains two items: an array of floating point values representing the various multiple fitnesses, and a flag (maximize) indicating whether higher is considered better. By default, isIdealFitness() always returns false; you might want to override that, though it'd be unusual -- what is the ideal fitness from the perspective of a pareto front?

The object also contains maximum and minimum fitness values suggested for the problem, on a per-objective basis. By default the maximum values are all 1.0 and the minimum values are all 0.0, but you can change these. Note that maximum does not mean "best" unless maximize is true.

The class also contains utility methods or computing pareto dominance, Pareto Fronts and Pareto Front Ranks, and distance in multiobjective space. The default comparison operators use Pareto Dominance, though this is often overridden by subclasses.

The fitness() method returns the maximum of the fitness values, which is clearly nonsensical: you should not be using this method.

Subclasses of this class may add certain auxiliary fitness measures which are printed out by MultiObjectiveStatistics along with the multiple objectives. To have these values printed out, override the getAuxiliaryFitnessNames() and getAuxiliaryFitnessValues() methods.

Parameters

base.`num-objectives` (else)`multi.num-objectives` int >= 1	(the number of fitnesses in the objectives array)
base.`maximize` bool = `true` (default) or `false`	(are higher values considered "better"?)

base.maximize.i bool = true (default) or false (are higher values considered "better"?). Overrides the all-objecgive maximization setting. base.max
double (1.0 default) (maximum fitness value for all objectives) base.max.i
double (1.0 default) (maximum fitness value for objective i. Overrides the all-objective maximum fitness.) base.min
double (0.0 (default) (minimum fitness value for all objectives) base.min.i
double = 0.0 (default) (minimum fitness value for objective i. Overrides the all-objective minimum fitness.)
Default Base
multi.fitness @author Sean Luke @version 1.1

        bypassFinalStatistics(state, result);  // just call super.super.finalStatistics(...)


        if (doFinal) state.output.println("\n\n\n PARETO FRONTS", statisticslog);
        for (int s = 0; s < state.population.subpops.length; s++)
            {
            @SuppressWarnings("unused")
      MultiObjectiveFitness typicalFitness = (MultiObjectiveFitness)(state.population.subpops[s].individuals[0].fitness);
            if (doFinal) state.output.println("\n\nPareto Front of Subpopulation " + s, statisticslog);


            // build front
            ArrayList front = MultiObjectiveFitness.partitionIntoParetoFront(state.population.subpops[s].individuals, null, null);


            // sort by objective[0]
            Object[] sortedFront = front.toArray();
            QuickSort.qsort(sortedFront, new SortComparator()
                {
                public boolean lt(Object a, Object b)
                    {
                    return (((MultiObjectiveFitness) (((Individual) a).fitness)).getObjective(0) < 
                        (((MultiObjectiveFitness) ((Individual) b).fitness)).getObjective(0));
                    }
                
                public boolean gt(Object a, Object b)
                    {
                    return (((MultiObjectiveFitness) (((Individual) a).fitness)).getObjective(0) > 
                        ((MultiObjectiveFitness) (((Individual) b).fitness)).getObjective(0));
                    }
                });
                        
            // print out front to statistics log
            if (doFinal)
                for (int i = 0; i < sortedFront.length; i++)
                    ((Individual)(sortedFront[i])).printIndividualForHumans(state, statisticslog);
                
            // write short version of front out to disk
            if (!silentFront)
                {
                if (state.population.subpops.length > 1)
                    state.output.println("Subpopulation " + s, frontLog);
                for (int i = 0; i < sortedFront.length; i++)
                    {
                    Individual ind = (Individual)(sortedFront[i]);
                    MultiObjectiveFitness mof = (MultiObjectiveFitness) (ind.fitness);
                    double[] objectives = mof.getObjectives();
        
                    String line = "";
                    for (int f = 0; f < objectives.length; f++)
                        line += (objectives[f] + " ");
                    state.output.println(line, frontLog);

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Related Classes of ec.multiobjective.MultiObjectiveFitness

ec.multiobjective.MultiObjectiveStatistics

ec.util.DecodeReturn

ec.util.Parameter

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