bool DESolver::Solve(int maxGenerations)
{
int generation;
int candidate;
bool bAtSolution;
bestEnergy = 1.0E20;
bAtSolution = false;
for (generation=0;(generation < maxGenerations) && !bAtSolution;generation++)
for (candidate=0; candidate < nPop; candidate++)
{
(this->*calcTrialSolution)(candidate);
trialEnergy = EnergyFunction(trialSolution,bAtSolution);
if (trialEnergy < popEnergy[candidate])
{
// New low for this candidate
popEnergy[candidate] = trialEnergy;
CopyVector(RowVector(population,candidate),trialSolution);
// Check if all-time low
if (trialEnergy < bestEnergy)
{
bestEnergy = trialEnergy;
CopyVector(bestSolution,trialSolution);
}
}
}
generations = generation;
return(bAtSolution);
}
int DESolver::Solve( int maxGenerations, int verbose )
{
int generation;
int candidate;
bool bAtSolution;
double relativeDeltas[3] = {100.0, 100.0, 100.0};
double lastBestEnergy;
bestEnergy = 1.0E20;
lastBestEnergy = bestEnergy;
bAtSolution = false;
for (generation = 0; (generation < maxGenerations) && !bAtSolution; generation++) {
for (candidate = 0; candidate < nPop; candidate++) {
// modified by PE
//(this->*calcTrialSolution)(candidate);
CalcTrialSolution(candidate);
// trialSolution now contains a newly generated parameter vector
// check for out-of-bounds values and generate random values w/in the bounds
CopyVector(oldValues, RowVector(population, candidate));
// oldValues is guaranteed to lie between minBounds and maxBounds
for (int j = 0; j < nDim; j++) {
if (trialSolution[j] < minBounds[j])
trialSolution[j] = minBounds[j] + RandomUniform(0.0,1.0)*(oldValues[j] - minBounds[j]);
if (trialSolution[j] > maxBounds[j])
trialSolution[j] = maxBounds[j] - RandomUniform(0.0,1.0)*(maxBounds[j] - oldValues[j]);
}
// Test our newly mutated/bred trial parameter vector
trialEnergy = EnergyFunction(trialSolution, bAtSolution);
if (trialEnergy < popEnergy[candidate]) {
// New low for this candidate
popEnergy[candidate] = trialEnergy;
CopyVector(RowVector(population,candidate), trialSolution);
// Check if all-time low
if (trialEnergy < bestEnergy) {
bestEnergy = trialEnergy;
CopyVector(bestSolution, trialSolution);
}
}
}
// Debugging printout code added by PE -- print an update every 10 generations
double relativeDeltaEnergy = 0.0;
if ((generation % 10) == 0) {
if (verbose > 0)
printf("\nGeneration %4d: bestEnergy = %12.10f", generation, bestEnergy);
if (generation == 20) {
relativeDeltaEnergy = fabs(1.0 - lastBestEnergy/bestEnergy);
relativeDeltas[0] = relativeDeltaEnergy;
if (verbose > 0)
printf(" (relative change = %e)", relativeDeltaEnergy);
}
else if (generation == 30) {
relativeDeltaEnergy = fabs(1.0 - lastBestEnergy/bestEnergy);
relativeDeltas[1] = relativeDeltas[0];
relativeDeltas[0] = relativeDeltaEnergy;
if (verbose > 0)
printf(" (relative change = %e)", relativeDeltaEnergy);
}
else if (generation >= 40) {
relativeDeltaEnergy = fabs(1.0 - lastBestEnergy/bestEnergy);
relativeDeltas[2] = relativeDeltas[1];
relativeDeltas[1] = relativeDeltas[0];
relativeDeltas[0] = relativeDeltaEnergy;
if (verbose > 0)
printf(" (relative change = %e)", relativeDeltaEnergy);
if (TestConverged(relativeDeltas, tolerance)) {
generations = generation;
bAtSolution = true;
return 1;
}
}
lastBestEnergy = bestEnergy;
}
if (isnan(bestEnergy)) {
// fprintf(stderr, "\n*** NaN-valued fit statistic detected (DE optimization)!\n");
printf("\n\tcandidate %d, bestEnergy = %f\n", candidate, bestEnergy);
}
}
generations = generation;
return 5;
}
