D:/Projekt/ECF_trunk/examples/FunctionMin/FunctionMinEvalOp_coco.cpp

#include <ecf/ECF.h>
#include "FunctionMinEvalOp.h"

// COCO
#include "bbobStructures.h" /* Include all declarations for BBOB calls */
double coco_optimum;
bool coco_initialized = false;



void FunctionMinEvalOp::registerParameters(StateP state)
{
    state->getRegistry()->registerEntry("function", (voidP) (new uint(1)), ECF::UINT);
}


bool FunctionMinEvalOp::initialize(StateP state)
{
    voidP sptr = state->getRegistry()->getEntry("function"); // get parameter value
    iFunction_ = *((uint*) sptr.get()); // convert from voidP to user defined type

    sptr = state->getRegistry()->getEntry("FloatingPoint.dimension");
    uint dim = *((uint*) sptr.get());

    //
    // COCO
    //
    if(coco_initialized) {
        fgeneric_finalize();
    }
    ParamStruct params = fgeneric_getDefaultPARAMS();

    /* set DIM, funcId, instanceId to initialize BBOB fgeneric */
    params.DIM = dim;
    params.funcId = iFunction_;
    params.instanceId = 1;

    /* call the BBOB initialization */
    fgeneric_initialize(params);
    coco_optimum = fgeneric_ftarget();
    coco_initialized = true;


    return true;
}


FitnessP FunctionMinEvalOp::evaluate(IndividualP individual)
{
    // evaluation creates a new fitness object using a smart pointer
    // in our case, we try to minimize the function value, so we use FitnessMin fitness (for minimization problems)
    FitnessP fitness (new FitnessMin);

    // we define FloatingPoint as the only genotype (in the configuration file)
    FloatingPoint::FloatingPoint* gen = (FloatingPoint::FloatingPoint*) individual->getGenotype().get();
    // (you can also use boost smart pointers:)
    //FloatingPointP gen = boost::dynamic_pointer_cast<FloatingPoint::FloatingPoint> (individual->getGenotype());

    // alternative encoding: Binary Genotype
    //Binary::Binary* gen = (Binary::Binary*) individual->getGenotype().get();
    //BinaryP gen = boost::dynamic_pointer_cast<Binary::Binary> (individual->getGenotype());

    // we implement the fitness function 'as is', without any translation
    // the number of variables is read from the genotype itself (size of 'realValue' vactor)
    double realTemp = 0, value = 0;


    //
    // COCO
    //
    value = fgeneric_evaluate(&(gen->realValue[0]));
    value -= coco_optimum;

    fitness->setValue(value);
    return fitness;
}