我正在使用名为ParadisEO的遗传算法库。我的算法运行正常，但我没有使用一个名为“存档”的库对象，它在算法的整个生命周期内存储非支配的个体（即最好的）。但是，当我尝试在与库关联的所有示例中声明归档对象时，我得到一个错误，上面写着“类型'moeoUnboundedArchive'必须实现继承的纯虚方法'moeoArchive :: operator（） “”。我不相信我已经覆盖了它！我已经在下面给出了我的代码的一部分，我相信它可能是相关的，如果有帮助的话，该库有充分记录here。
我很感激您可以提出任何帮助！
我的代码是：
#include <stdio.h>
#include <stdlib.h>
#include <vector>
#include <eo>
#include <moeo>
class wetland_vector : public std::vector<int> {
public:
wetland_vector() : std::vector<int> (7,0) {}
};
std::istream& operator>>(std::istream& is, wetland_vector& q) {
for (unsigned int i = 0; i < q.size(); ++i) {
is >> q[i];
}
return is;
}
std::ostream& operator<<(std::ostream& os, const wetland_vector& q) {
os << q[0];
for (unsigned int i = 1; i < q.size(); ++i) {
os << " " << q[i];
}
os << " ";
return os;
}
class wetland_init : public eoInit<wetland_vector> {
public:
void operator()(wetland_vector& wetland_vector) {
wetland_vector[0] = rng.random(10);
wetland_vector[1] = rng.random(10);
wetland_vector[2] = rng.random(100);
wetland_vector[3] = rng.random(25);
wetland_vector[4] = rng.random(100);
wetland_vector[5] = rng.random(25);
wetland_vector[6] = rng.random(25);
}
};
class objective_vector_traits : public moeoObjectiveVectorTraits
{
public:
static bool minimizing (int i)
{
return true;
}
static bool maximizing (int i)
{
return false;
}
static unsigned int nObjectives ()
{
return 2;
}
};
typedef moeoRealObjectiveVector<objective_vector_traits> objective_vector;
class plan_vector : public moeoVector<objective_vector,wetland_vector,double,double>{
};
double dummy_evaluation_function_0(plan_vector& plan_vector){
int sum = 0;
for(unsigned int i = 0; i < plan_vector.size(); i++){
for(unsigned int j = 0; j < plan_vector[i].size(); j++){
sum += plan_vector[i][j];
}
}
return sum;
}
double dummy_evaluation_function_1(plan_vector& plan_vector){
int sum = 0;
for(unsigned int i = 0; i < plan_vector.size(); i++){
for(unsigned int j = 0; j < plan_vector[i].size(); j++){
sum += plan_vector[i][j];
}
}
return sum*sum;
}
class plan_vector_evaluation_object : public moeoEvalFunc <plan_vector>
{
public:
void operator () (plan_vector& plan_vector)
{
objective_vector objective_vector;
objective_vector[0] = dummy_evaluation_function_0(plan_vector);
objective_vector[1] = dummy_evaluation_function_1(plan_vector);
plan_vector.objectiveVector(objective_vector);
}
};
class eoMutate : public eoMonOp<plan_vector> {
bool operator() (plan_vector& plan_vector) {
int which_wet_vector = rng.random(plan_vector.size());
int which_pos = rng.random(plan_vector[which_wet_vector].size());
plan_vector[which_wet_vector][which_pos] = rng.random(10);
return true;
};
};
class eoQuadCross : public eoQuadOp<plan_vector> {
public:
bool operator() (plan_vector& vector_a, plan_vector& vector_b) {
int a_size = vector_a.size();
int b_size = vector_b.size();
int min_chrom_length = 0;
if(a_size <= b_size){
min_chrom_length = a_size;
}
if(b_size < a_size){
min_chrom_length = b_size;
}
unsigned int crossover_position = rng.random(min_chrom_length);
for(unsigned int i = 0; i < crossover_position; i++){
std::vector<int> a_vec = vector_a[i];
std::vector<int> b_vec = vector_b[i];
vector_a[i].clear();
for(unsigned int j = 0; j < b_vec.size(); j++){
vector_a[i].push_back(b_vec[j]);
}
vector_b[i].clear();
for(unsigned int k = 0; k < a_vec.size(); k++){
vector_b[i].push_back(a_vec[k]);
}
}
return true;
}
};
int main() {
int minimum_chromosome_length = 1;
int maximum_chromosome_length = 20;
int pop_size = 20;
int max_gen = 50;
//Prereq objects
wetland_init wetland_init;
eoInitVariableLength<plan_vector> plan_vector_init(minimum_chromosome_length, maximum_chromosome_length, wetland_init);
eoPop<plan_vector> pop(pop_size, plan_vector_init);
eoMutate mutate;
eoQuadCross crossover;
eoSGATransform<plan_vector> transform(crossover,0.75,mutate,0.05);
plan_vector_evaluation_object eval;
eoGenContinue<plan_vector> generation_count(max_gen);
eoCheckPoint<plan_vector> checkpoint(generation_count);
//THE PROBLEM IS HERE!!
moeoUnboundedArchive<plan_vector> archive;
moeoArchiveUpdater<plan_vector> updater(archive,pop);
checkpoint.add(updater);
//Set algorithm and go
moeoNSGAII<plan_vector> genetic_algorithm(checkpoint,eval,transform);
genetic_algorithm(pop);
for(unsigned int i = 0; i < archive.size(); i++){
for(unsigned int j = 0; j < archive[i].size(); j++){
for(unsigned int k = 0; k < archive[i][j].size(); k++){
std::cout << archive[i][j][k] << " ";
}
std::cout << std::endl;
}
}
return 0;
}
moeoUnboundedArchive.h是：
template < class MOEOT >
class moeoUnboundedArchive : public moeoArchive < MOEOT >
{
public:
/**
* The type of an objective vector for a solution
*/
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
/**
* Default ctor.
* The moeoObjectiveVectorComparator used to compare solutions is based on Pareto dominance
* @param _replace boolean which determine if a solution with the same objectiveVector than another one, can replace it or not
*/
moeoUnboundedArchive(bool _replace=true) : moeoArchive < MOEOT >(_replace) {}
/**
* Ctor
* @param _comparator the moeoObjectiveVectorComparator used to compare solutions
* @param _replace boolean which determine if a solution with the same objectiveVector than another one, can replace it or not
*/
moeoUnboundedArchive(moeoObjectiveVectorComparator < ObjectiveVector > & _comparator, bool _replace=true) : moeoArchive < MOEOT >(_comparator, _replace) {}
/**
* Updates the archive with a given individual _moeo
* @param _moeo the given individual
* @return true if _moeo is added to the archive
*/
bool operator()(const MOEOT & _moeo)
{
return this->update(_moeo);
}
/**
* Updates the archive with a given population _pop
* @param _pop the given population
* @return true if a _pop[i] is added to the archive
*/
bool operator()(const eoPop < MOEOT > & _pop)
{
return this->update(_pop);
}
};
最后，moeoArchive.h是：
template < class MOEOT >
class moeoArchive : public eoPop < MOEOT >, public eoUF < const MOEOT &, bool>, public eoUF < const eoPop < MOEOT > &, bool>
{
public:
using eoPop < MOEOT > :: size;
using eoPop < MOEOT > :: operator[];
using eoPop < MOEOT > :: back;
using eoPop < MOEOT > :: pop_back;
/**
* The type of an objective vector for a solution
*/
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
/**
* Default ctor.
* The moeoObjectiveVectorComparator used to compare solutions is based on Pareto dominance
* @param _replace boolean which determine if a solution with the same objectiveVector than another one, can replace it or not
*/
moeoArchive(bool _replace=true) : eoPop < MOEOT >(), comparator(paretoComparator), replace(_replace)
{}
/**
* Ctor
* @param _comparator the moeoObjectiveVectorComparator used to compare solutions
* @param _replace boolean which determine if a solution with the same objectiveVector than another one, can replace it or not
*/
moeoArchive(moeoObjectiveVectorComparator < ObjectiveVector > & _comparator, bool _replace=true) : eoPop < MOEOT >(), comparator(_comparator), replace(_replace)
{}
/**
* Returns true if the current archive dominates _objectiveVector according to the moeoObjectiveVectorComparator given in the constructor
* @param _objectiveVector the objective vector to compare with the current archive
*/
bool dominates (const ObjectiveVector & _objectiveVector) const
{
for (unsigned int i = 0; i<size(); i++)
{
// if _objectiveVector is dominated by the ith individual of the archive...
if ( comparator(_objectiveVector, operator[](i).objectiveVector()) )
{
return true;
}
}
return false;
}
/**
* Returns true if the current archive already contains a solution with the same objective values than _objectiveVector
* @param _objectiveVector the objective vector to compare with the current archive
*/
bool contains (const ObjectiveVector & _objectiveVector) const
{
for (unsigned int i = 0; i<size(); i++)
{
if (operator[](i).objectiveVector() == _objectiveVector)
{
return true;
}
}
return false;
}
/**
* Updates the archive with a given individual _moeo
* @param _moeo the given individual
* @return if the _moeo is added to the archive
*/
virtual bool operator()(const MOEOT & _moeo) = 0;
/**
* Updates the archive with a given population _pop
* @param _pop the given population
* @return if at least one _pop[i] is added to the archive
*/
virtual bool operator()(const eoPop < MOEOT > & _pop) = 0;
/**
* Returns true if the current archive contains the same objective vectors than the given archive _arch
* @param _arch the given archive
*/
bool equals (const moeoArchive < MOEOT > & _arch)
{
for (unsigned int i=0; i<size(); i++)
{
if (! _arch.contains(operator[](i).objectiveVector()))
{
return false;
}
}
for (unsigned int i=0; i<_arch.size() ; i++)
{
if (! contains(_arch[i].objectiveVector()))
{
return false;
}
}
return true;
}
protected:
/**
* Updates the archive with a given individual _moeo
* @param _moeo the given individual
*/
bool update(const MOEOT & _moeo)
{
// first step: removing the dominated solutions from the archive
for (unsigned int j=0; j<size();)
{
// if the jth solution contained in the archive is dominated by _moeo
if ( comparator(operator[](j).objectiveVector(), _moeo.objectiveVector()) )
{
operator[](j) = back();
pop_back();
}
else if (replace && (_moeo.objectiveVector() == operator[](j).objectiveVector()))
{
operator[](j) = back();
pop_back();
}
else
{
j++;
}
}
// second step: is _moeo dominated?
bool dom = false;
for (unsigned int j=0; j<size(); j++)
{
// if _moeo is dominated by the jth solution contained in the archive
if ( comparator(_moeo.objectiveVector(), operator[](j).objectiveVector()) )
{
dom = true;
break;
}
else if (!replace && (_moeo.objectiveVector() == operator[](j).objectiveVector()) )
{
dom = true;
break;
}
}
if (!dom)
{
this->push_back(_moeo);
}
return !dom;
}
/**
* Updates the archive with a given population _pop
* @param _pop the given population
*/
bool update(const eoPop < MOEOT > & _pop)
{
bool res = false;
bool tmp = false;
for (unsigned int i=0; i<_pop.size(); i++)
{
tmp = (*this).update(_pop[i]);
res = tmp || res;
}
return res;
}
/** The moeoObjectiveVectorComparator used to compare solutions */
moeoObjectiveVectorComparator < ObjectiveVector > & comparator;
/** A moeoObjectiveVectorComparator based on Pareto dominance (used as default) */
moeoParetoObjectiveVectorComparator < ObjectiveVector > paretoComparator;
/** boolean */
bool replace;
};