ReturnFlag CPSORSwarm::run_(){
#ifdef OFEC_CONSOLE
if(Global::msp_global->m_runId==0){
mSingleObj::getSingleObj()->setProgrOutputFlag(true);
if(mMultiModal::getPopInfor())
mMultiModal::getPopInfor()->setOutProgFlag(true);
}
#endif // OFEC_CONSOLE
createSubswarms();
ReturnFlag r_flag=Return_Normal;
while(!ifTerminating()){
for(auto &swarm:m_subPop){
if(swarm->m_popsize==0) continue;
r_flag=swarm->evolve();
if(r_flag==Return_Terminate) break;
handleReturnFlagAll(r_flag);
HANDLE_RETURN_FLAG(r_flag)
#ifdef OFEC_DEMON
vector<Algorithm*> vp;
for(auto &it:m_subPop){
vp.push_back(it.get());
}
msp_buffer->updateBuffer_(&vp);
#endif
}
if(r_flag==Return_Terminate) break;
//cout<<Global::msp_global->mp_problem->getEvaluations()<<" "<<getNumPops()<<" "<<m_subPop[findBestPop(1)]->m_best[0]->obj(0)<<endl;
measureMultiPop();
if(m_subPop.size()>1){
while(removeOverlapping()!=-1);
for(auto it=m_subPop.begin();it!=m_subPop.end();++it) (*it)->checkOverCrowd(m_subSize);
for(decltype(m_subPop.size()) i=0;i<m_subPop.size();i++){
if(m_subPop[i]->isConverged(0.0001)){
deletePopulation(i);
i--;
}
}
}
if(Global::msp_global->m_totalNumIndis<m_initialSize*m_diversityDegree){
initialize();
if(ifTerminating()) break;
createSubswarms();
}
}
return Return_Terminate;
}
ReturnFlag CPSOH::run_()
{
ReturnFlag rf=Return_Normal;
#ifdef OFEC_CONSOLE
if(Global::msp_global->m_runId==0){
mSingleObj::getSingleObj()->setProgrOutputFlag(true);
if(mMultiModal::getPopInfor())
mMultiModal::getPopInfor()->setOutProgFlag(true);
}
#endif // OFEC_CONSOLE
while(!ifTerminating())
{
//cout<<"Run: "<<Global::msp_global->m_runId<<" "<<Global::msp_global->mp_problem->getEvaluations()<<endl;
rf=evolve();
#ifdef OFEC_CONSOLE
if(mMultiModal::getPopInfor()){
int peaksf;
peaksf=CAST_PROBLEM_CONT->getGOpt().getNumGOptFound();
mMultiModal::getPopInfor()->input(Global::msp_global.get(), Global::msp_global->mp_problem->getEvaluations(),\
Global::msp_global->m_totalNumIndis,1,peaksf,\
CAST_PROBLEM_CONT->getGOpt().getNumOpt(),0,0,0,0,\
0,0,CAST_PROBLEM_CONT->getGOpt().isAllFound());
}
#endif
if(rf==Return_Terminate) return rf;
}
return rf;
}
ReturnFlag ACS::run_()
{
int i, j, dim;
initializeSystem();
dim = m_pop[0]->getNumDim();
m_iter = 0;
if (m_stopCriterion == MIN_COVER){
dynamic_cast<TermMean*>(m_term.get())->initialize(DBL_MAX);
}
while (!ifTerminating())
{
#ifdef OFEC_DEMON
for (i = 0; i<this->getPopSize(); i++)
updateBestArchive(this->m_pop[i]->self());
vector<Algorithm*> vp;
vp.push_back(this);
msp_buffer->updateBuffer_(&vp);
#endif
for (i = 0; i < m_popsize; i++)
{
for (j = 1; j < dim; j++)
{
double q = Global::msp_global->mp_uniformAlg->Next();
if (q <= m_Q)
m_pop[i]->selectNextCity_Greedy(mvv_phero, m_beta);
else
m_pop[i]->selectNextCity_Pro(mvv_phero, m_beta);
local_updatePheromeno(i);
}
local_updatePheromeno(i, true);
}
global_updatePheromeno();
resetAntsInfo();
++m_iter;
if (m_stopCriterion == MIN_COVER) {
dynamic_cast<TermMean*>(m_term.get())->countSucIter(mean());
}
//cout<<" "<<Global::msp_global->mp_problem->getBestSolutionSoFar().getObjDistance(CAST_TSP->getGOpt()[0].data().m_obj)<<" "<<m_stopCount<<endl;
#ifdef OFEC_CONSOLE
double tempdif = 0;
for (int i = 0; i < m_popsize; i++)
tempdif += m_pop[i]->self().getDistance(Solution<CodeVInt>::getBestSolutionSoFar());
tempdif /= m_popsize;
double impr = static_cast<double>(m_impRadio) / m_popsize;
OptimalEdgeInfo::getOptimalEdgeInfo()->recordiffAndImp(Global::msp_global->m_runId, Global::msp_global->mp_problem->getEvaluations(), fabs(tempdif), impr);
#endif
}
#ifdef OFEC_CONSOLE
vector<int> bestIdx = findBest();
OptimalEdgeInfo::getOptimalEdgeInfo()->recordEdgeInfo<Ant>(Global::msp_global.get(), Solution<CodeVInt>::getBestSolutionSoFar(), m_pop, m_num, m_popsize, m_saveFre, false);
OptimalEdgeInfo::getOptimalEdgeInfo()->recordLastInfo(Global::msp_global->m_runId, Global::msp_global->mp_problem->getEvaluations());
#endif
return Return_Terminate;
}
ReturnFlag NFishSwarm::run_(){
ReturnFlag rf=Return_Normal;
Global::msp_global->mp_problem->setValidateMode(VALIDATION_SETTOBOUND);
while(!ifTerminating()){
g_mutexStream.lock();
// cout<<Global::msp_global->m_runId<<" "<<Global::msp_global->mp_problem->getEvaluations()<<" "<<m_best[0]->obj(0)<<endl;
g_mutexStream.unlock();
#ifdef OFEC_DEMON
vector<Algorithm*> vp;
vp.push_back(this);
msp_buffer->updateBuffer_(&vp);
#endif
rf=evolve();
}
return rf;
}
ReturnFlag LinkageDE_::run_() {
ReturnFlag rf = Return_Normal;
#ifdef OFEC_CONSOLE
if (Global::msp_global->m_runId == 0) {
mSingleObj::getSingleObj()->setProgrOutputFlag(true);
if (mMultiModal::getPopInfor())
mMultiModal::getPopInfor()->setOutProgFlag(true);
}
#endif // OFEC_CONSOLE
initilizeMemory();
initilizeCurPop();
while (!ifTerminating()) {
/*g_mutexStream.lock();
cout<<Global::msp_global->m_runId<<" "<<Global::msp_global->mp_problem->getEvaluations()<<" "<<m_best[0]->obj(0)<<endl;
g_mutexStream.unlock();*/
rf = this->evolve();
#ifdef OFEC_DEMON
vector<Algorithm*> vp;
vp.push_back(this);
msp_buffer->updateBuffer_(&vp);
#endif
if (rf != Return_Normal) handleReturnFlag(rf);
updateMemory();
#ifdef OFEC_CONSOLE
if (mMultiModal::getPopInfor()) {
int peaksf;
peaksf = CAST_PROBLEM_CONT->getGOpt().getNumGOptFound();
mMultiModal::getPopInfor()->input(Global::msp_global.get(), Global::msp_global->mp_problem->getEvaluations(), \
Global::msp_global->m_totalNumIndis, 1, peaksf, \
CAST_PROBLEM_CONT->getGOpt().getNumOpt(), 0, 0, 0, 0, \
0, 0, CAST_PROBLEM_CONT->getGOpt().isAllFound());
}
#endif
if (rf == Return_Terminate) break;
}
return rf;
}
ReturnFlag CRDEPopulation::run_()
{
#ifdef OFEC_CONSOLE
if(Global::msp_global->m_runId==0){
mSingleObj::getSingleObj()->setProgrOutputFlag(true);
if(mMultiModal::getPopInfor())
mMultiModal::getPopInfor()->setOutProgFlag(true);
}
#endif // OFEC_CONSOLE
ReturnFlag rf=Return_Normal;
while(!ifTerminating())
{
// cout<<Global::msp_global->mp_problem->getEvaluations()<<endl;
#ifdef OFEC_DEMON
vector<Algorithm*> vp;
vp.push_back(this);
msp_buffer->updateBuffer_(&vp);
#endif
rf=evolve();
#ifdef OFEC_CONSOLE
if(mMultiModal::getPopInfor()){
int peaksf;
peaksf=CAST_PROBLEM_CONT->getGOpt().getNumGOptFound();
mMultiModal::getPopInfor()->input(Global::msp_global.get(), Global::msp_global->mp_problem->getEvaluations(),\
Global::msp_global->m_totalNumIndis,1,peaksf,\
CAST_PROBLEM_CONT->getGOpt().getNumOpt(),0,0,0,0,\
0,0,CAST_PROBLEM_CONT->getGOpt().isAllFound());
}
#endif
if(rf==Return_Terminate) break;
}
return rf;
}
ReturnFlag CMAES::run_(){
#ifdef OFEC_CONSOLE
if (Global::msp_global->m_runId == 0) {
mSingleObj::getSingleObj()->setProgrOutputFlag(true);
if (mMultiModal::getPopInfor())
mMultiModal::getPopInfor()->setOutProgFlag(true);
}
#endif // OFEC_CONSOLE
cmaes_t evo; /* an CMA-ES type struct or "object" */
double *arFunvals, *const*pop, *xfinal;
int i;
int numDim = Global::msp_global->mp_problem->getNumDim();
/* Initialize everything into the struct evo, 0 means default */
arFunvals = cmaes_init(&evo, numDim, NULL, NULL, 0, m_pop.size(), initialsFilePathName.c_str());//"cmaes_initials.par"
//printf("%s\n", cmaes_SayHello(&evo));
cmaes_ReadSignals(&evo, signalsFilePathName.c_str()); /* "cmaes_signals.par"write header and initial values */
/* Iterate until stop criterion holds */
while (!ifTerminating())/*!cmaes_TestForTermination(&evo)*/
{
/* generate lambda new search points, sample population */
pop = cmaes_SamplePopulation(&evo); /* do not change content of pop */
for (i = 0; i < cmaes_Get(&evo, "lambda"); ++i) {
copy(pop[i], m_pop[i].data());
}
for (i = 0; i < cmaes_Get(&evo, "popsize"); ++i) {
/* You may resample the solution i until it lies within the
feasible domain here, e.g. until it satisfies given
box constraints (variable boundaries). The function
is_feasible() needs to be user-defined.
Assumptions: the feasible domain is convex, the optimum
is not on (or very close to) the domain boundary,
initialX is feasible (or in case typicalX +- 2*initialStandardDeviations
is feasible) and initialStandardDeviations is (are)
sufficiently small to prevent quasi-infinite looping.
*/
while (!Global::msp_global->mp_problem->isValid(m_pop[i].data())) {
cmaes_ReSampleSingle(&evo, i);
copy(pop[i], m_pop[i].data());
}
}
/* evaluate the new search points using fitfun */
for (i = 0; i < cmaes_Get(&evo, "lambda"); ++i) {
arFunvals[i] = fitCompute(m_pop[i]);
}
/* update the search distribution used for cmaes_SamplePopulation() */
cmaes_UpdateDistribution(&evo, arFunvals);
/* read instructions for printing output or changing termination conditions */
cmaes_ReadSignals(&evo, signalsFilePathName.c_str());//"cmaes_signals.par"
fflush(stdout); /* useful in MinGW */
#ifdef OFEC_CONSOLE
if (mMultiModal::getPopInfor()) {
int peaksf;
peaksf = CAST_PROBLEM_CONT->getGOpt().getNumGOptFound();
mMultiModal::getPopInfor()->input(Global::msp_global.get(), Global::msp_global->mp_problem->getEvaluations(), \
Global::msp_global->m_totalNumIndis, 1, peaksf, \
CAST_PROBLEM_CONT->getGOpt().getNumOpt(), 0, 0, 0, 0, \
0, 0, CAST_PROBLEM_CONT->getGOpt().isAllFound());
}
#endif
//cout << cmaes_Get(&evo, "fbestever") <<" "<<Global::msp_global->mp_problem->getEvaluations()<< endl;
}
//printf("Stop:\n%s\n", cmaes_TestForTermination(&evo)); /* print termination reason */
//cmaes_WriteToFile(&evo, "all", "allcmaes.dat"); /* write final results */
/* get best estimator for the optimum, xmean */
xfinal = cmaes_GetNew(&evo, "xmean"); /* "xbestever" might be used as well */
cmaes_exit(&evo); /* release memory */
/* do something with final solution and finally release memory */
free(xfinal);
return Return_Terminate;
}
ReturnFlag GSTM::run_()
{
GAPopulation<CodeVInt, GAIndividual<CodeVInt>> subPopul(m_popsize);
GAIndividual<CodeVInt> ia, ib;
int i, n;
double p;
int flag, flag1;
double bestlen = DBL_MAX;
vector<int> arr(m_numDim);
dynamic_cast<TermMean*>(m_term.get())->initialize(mean());
while (!ifTerminating())
{
/*if(Global::msp_global->mp_problem->getEvaluations()/m_saveFre<m_num){
mean<<diffEdges()<<" "<<Global::msp_global->mp_problem->getEvaluations()<<endl;
}*/
#ifdef OFEC_DEMON
for (i = 0; i<this->getPopSize(); i++)
updateBestArchive(this->m_pop[i]->self());
vector<Algorithm*> vp;
vp.push_back(this);
msp_buffer->updateBuffer_(&vp);
#endif
//cout<<Global::msp_global->mp_problem->getEvaluations()<<endl;
n = 0;
while (n<m_popsize)
{
flag = 0;
flag1 = 0;
selection(ia, ib);
p = Global::msp_global->mp_uniformAlg->Next();
if (p <= m_PC)
{
*subPopul.getPop()[n++] = crossover(ia, ib);
flag = 1;
}
if (flag == 0)
{
if (n<m_popsize - 1)
{
*subPopul.getPop()[n++] = ia;
*subPopul.getPop()[n++] = ib;
}
else
{
*subPopul.getPop()[n++] = ia;
flag1 = 1;
}
}
p = Global::msp_global->mp_uniformAlg->Next();
if (p <= m_PM)
{
if (flag == 1 || flag1 == 1) mutation(*subPopul.getPop()[n - 1]);
else
{
mutation(*subPopul.getPop()[n - 2]);
mutation(*subPopul.getPop()[n - 1]);
}
}
}
for (i = 0; i<m_popsize; i++)
subPopul.getPop()[i]->evaluate();
*(static_cast<GAPopulation<CodeVInt, GAIndividual<CodeVInt>>*>(this)) = subPopul;
#ifdef OFEC_CONSOLE
OptimalEdgeInfo::getOptimalEdgeInfo()->recordEdgeInfo<GAIndividual<CodeVInt>>(Global::msp_global.get(), Solution<CodeVInt>::getBestSolutionSoFar(), m_pop, m_num, m_popsize, m_saveFre);
#endif
m_iter++;
}
#ifdef OFEC_CONSOLE
OptimalEdgeInfo::getOptimalEdgeInfo()->recordEdgeInfo<GAIndividual<CodeVInt>>(Global::msp_global.get(), Solution<CodeVInt>::getBestSolutionSoFar(), m_pop, m_num, m_popsize, m_saveFre, false);
OptimalEdgeInfo::getOptimalEdgeInfo()->recordLastInfo(Global::msp_global->m_runId, Global::msp_global->mp_problem->getEvaluations());
#endif
return Return_Terminate;
}
