ReturnFlag CPSOSubSwarm::evolve(){
if(this->m_popsize<1) return Return_Normal;
Solution<CodeVReal> t;
ReturnFlag r_flag=Return_Normal;
for(int i=0;i<this->m_popsize;i++){
t=this->m_pop[i]->self();
bool flag=false;
r_flag=this->m_pop[i]->moveBound(this->m_pop[i]->m_pbest,this->getNearestBest(this->m_pop[i]->self()),m_W,m_C1,m_C2);//
if(this->m_pop[i]->self()>this->m_pop[i]->m_pbest){
this->m_pop[i]->m_pbest=this->m_pop[i]->self();
flag=this->updateBestArchive(this->m_pop[i]->self());
}
if(r_flag!=Return_Normal) break;
if(!flag&&this->m_pop[i]->self()>t){
r_flag=updateBest(i,1.0);
}
if(r_flag!=Return_Normal) { break;}
}
if(r_flag==Return_Normal){
this->m_evoNum++;
double ratio=Global::msp_global->mp_problem->getEvaluations()%CAST_PROBLEM_DYN->getChangeFre()/static_cast<double>(CAST_PROBLEM_DYN->getChangeFre());
m_W=m_maxW-(m_maxW-m_minW)*ratio;
}
computeCenter();
updateCurRadius(true);
return r_flag;
}
ReturnFlag RASPSO11::evolve() {
//lbest model with an adaptive random topology
ReturnFlag rf = Return_Normal;
if (m_popsize<1) return rf;
vector<int> rindex(m_popsize);
Global::msp_global->initializeRandomArray(rindex, m_popsize); //generate a permutation of particle index
setNeibourhood();
m_noCurActive = 0;
m_impr = 0;
m_flag[0] = false;
for (int i = 0; i<m_popsize; i++) {
if (Global::msp_global->mp_uniformAlg->Next()>m_pop[rindex[i]]->fitness()) {
m_pop[rindex[i]]->setActive(false);
m_curActive[rindex[i]] = false;
continue;
}
Solution<CodeVReal> *l = &neighborBest(rindex[i]);
if (l != &m_pop[rindex[i]]->pbest())
rf = m_pop[rindex[i]]->move(m_W, m_C1, m_C2, l, true);
else rf = m_pop[rindex[i]]->move(m_W, m_C1, m_C2, 0, true);
if (m_pop[rindex[i]]->self()>(m_pop[rindex[i]]->pbest())) {
m_pop[rindex[i]]->pbest() = m_pop[rindex[i]]->self();
m_pop[rindex[i]]->setImpr(true);
if (updateBestArchive(m_pop[rindex[i]]->self())) {
m_impr++;
m_flag[0] = true;
}
}else m_pop[rindex[i]]->setImpr(false);
m_pop[rindex[i]]->setActive(true);
m_noCurActive++;
m_curActive[rindex[i]] = true;
handleReturnFlag(rf);
HANDLE_RETURN_FLAG(rf)
}
updateInfor();
updateCurRadius();
m_iter++;
m_preActive = m_curActive;
m_noPreActive = m_noCurActive;
return rf;
}
ReturnFlag NFishSwarm::evolve(){
ReturnFlag rf=Return_Normal;
//new prey behavior
for(auto &fish:m_pop){
for(int i=0;i<m_tryNumber;++i){
rf=fish->prey(m_visual);
if(rf!=Return_Normal) return rf;
updateBestArchive(fish->self());
}
}
//new follow behavior
for(auto &fish:m_pop){
rf=fish->follow(*m_best[0],m_visual);
if(rf!=Return_Normal) return rf;
updateBestArchive(fish->self());
}
//new swarm behevior
computeCenter();
findBest();
for(auto &fish:m_pop){
if(m_center>fish->self()){
if(fish->m_index!=m_bestIdx[0]){
rf=fish->swarm(m_center,m_visual);
if(rf!=Return_Normal) return rf;
}else{
fish->self()=m_center;
}
updateBestArchive(fish->self());
}
}
updateVisual();
updateCurRadius();
m_iter++;
return rf;
}
ReturnFlag SPSO11::evolve(){
//lbest model with an adaptive random topology
ReturnFlag rf=Return_Normal;
if(m_popsize<1) return rf;
vector<int> rindex(m_popsize);
Global::msp_global->initializeRandomArray(rindex,m_popsize); //generate a permutation of particle index
setNeibourhood();
m_impr=0;
for(int i=0;i<m_popsize;i++){
Solution<CodeVReal> *l = &neighborBest(rindex[i]);
if (l != &m_pop[rindex[i]]->m_pbest)
rf = m_pop[rindex[i]]->move(m_W, m_C1, m_C2, l, true);
else rf = m_pop[rindex[i]]->move(m_W, m_C1, m_C2, 0, true);
if(m_pop[rindex[i]]->self()>(m_pop[rindex[i]]->m_pbest)){
m_pop[rindex[i]]->m_pbest=m_pop[rindex[i]]->self();
if(updateBestArchive(m_pop[rindex[i]]->self())){
m_impr++;
}
}
handleReturnFlag(rf);
HANDLE_RETURN_FLAG(rf)
}
updateCurRadius();
m_iter++;
return rf;
}
