Particle swarm optimization: Difference between revisions
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GlobalBestPosition: -0.5134004259016365,-1.5512442672625184
GlobalBestValue: -1.9114053788600853</lang>
=={{header|Java}}==
{{trans|Kotlin}}
<lang java>import java.util.Arrays;
import java.util.Objects;
import java.util.Random;
import java.util.function.Function;
public class App {
static class Parameters {
double omega;
double phip;
double phig;
Parameters(double omega, double phip, double phig) {
this.omega = omega;
this.phip = phip;
this.phig = phig;
}
}
static class State {
int iter;
double[] gbpos;
double gbval;
double[] min;
double[] max;
Parameters parameters;
double[][] pos;
double[][] vel;
double[][] bpos;
double[] bval;
int nParticles;
int nDims;
State(int iter, double[] gbpos, double gbval, double[] min, double[] max, Parameters parameters, double[][] pos, double[][] vel, double[][] bpos, double[] bval, int nParticles, int nDims) {
this.iter = iter;
this.gbpos = gbpos;
this.gbval = gbval;
this.min = min;
this.max = max;
this.parameters = parameters;
this.pos = pos;
this.vel = vel;
this.bpos = bpos;
this.bval = bval;
this.nParticles = nParticles;
this.nDims = nDims;
}
void report(String testfunc) {
System.out.printf("Test Function : %s\n", testfunc);
System.out.printf("Iterations : %d\n", iter);
System.out.printf("Global Best Position : %s\n", Arrays.toString(gbpos));
System.out.printf("Global Best value : %.15f\n", gbval);
}
}
private static State psoInit(double[] min, double[] max, Parameters parameters, int nParticles) {
int nDims = min.length;
double[][] pos = new double[nParticles][];
for (int i = 0; i < nParticles; ++i) {
pos[i] = min.clone();
}
double[][] vel = new double[nParticles][nDims];
double[][] bpos = new double[nParticles][];
for (int i = 0; i < nParticles; ++i) {
bpos[i] = min.clone();
}
double[] bval = new double[nParticles];
for (int i = 0; i < bval.length; ++i) {
bval[i] = Double.POSITIVE_INFINITY;
}
int iter = 0;
double[] gbpos = new double[nDims];
for (int i = 0; i < gbpos.length; ++i) {
gbpos[i] = Double.POSITIVE_INFINITY;
}
double gbval = Double.POSITIVE_INFINITY;
return new State(iter, gbpos, gbval, min, max, parameters, pos, vel, bpos, bval, nParticles, nDims);
}
private static Random r = new Random();
private static State pso(Function<double[], Double> fn, State y) {
Parameters p = y.parameters;
double[] v = new double[y.nParticles];
double[][] bpos = new double[y.nParticles][];
for (int i = 0; i < y.nParticles; ++i) {
bpos[i] = y.min.clone();
}
double[] bval = new double[y.nParticles];
double[] gbpos = new double[y.nDims];
double gbval = Double.POSITIVE_INFINITY;
for (int j = 0; j < y.nParticles; ++j) {
// evaluate
v[j] = fn.apply(y.pos[j]);
// update
if (v[j] < y.bval[j]) {
bpos[j] = y.pos[j];
bval[j] = v[j];
} else {
bpos[j] = y.bpos[j];
bval[j] = bval[j];
}
if (bval[j] < gbval) {
gbval = bval[j];
gbpos = bpos[j];
}
}
double rg = r.nextDouble();
double[][] pos = new double[y.nParticles][y.nDims];
double[][] vel = new double[y.nParticles][y.nDims];
for (int j = 0; j < y.nParticles; ++j) {
// migrate
double rp = r.nextDouble();
boolean ok = true;
Arrays.fill(vel[j], 0.0);
Arrays.fill(pos[j], 0.0);
for (int k = 0; k < y.nDims; ++k) {
vel[j][k] = p.omega * y.vel[j][k] +
p.phip * rp * (bpos[j][k] - y.pos[j][k]) +
p.phig * rg * (gbpos[k] - y.pos[j][k]);
pos[j][k] = y.pos[j][k] + vel[j][k];
ok = ok && y.min[k] < pos[j][k] && y.max[k] > pos[j][k];
}
if (!ok) {
for (int k = 0; k < y.nDims; ++k) {
pos[j][k] = y.min[k] + (y.max[k] - y.min[k]) * r.nextDouble();
}
}
}
int iter = 1 + y.iter;
return new State(
iter, gbpos, gbval, y.min, y.max, y.parameters,
pos, vel, bpos, bval, y.nParticles, y.nDims
);
}
private static State iterate(Function<double[], Double> fn, int n, State y) {
State r = y;
if (n == Integer.MAX_VALUE) {
State old = y;
while (true) {
r = pso(fn, r);
if (Objects.equals(r, old)) break;
old = r;
}
} else {
for (int i = 0; i < n; ++i) {
r = pso(fn, r);
}
}
return r;
}
private static double mccormick(double[] x) {
double a = x[0];
double b = x[1];
return Math.sin(a + b) + (a - b) * (a - b) + 1.0 + 2.5 * b - 1.5 * a;
}
private static double michalewicz(double[] x) {
int m = 10;
int d = x.length;
double sum = 0.0;
for (int i = 1; i < d; ++i) {
double j = x[i - 1];
double k = Math.sin(i * j * j / Math.PI);
sum += Math.sin(j) * Math.pow(k, 2.0 * m);
}
return -sum;
}
public static void main(String[] args) {
State state = psoInit(
new double[]{-1.5, -3.0},
new double[]{4.0, 4.0},
new Parameters(0.0, 0.6, 0.3),
100
);
state = iterate(App::mccormick, 40, state);
state.report("McCormick");
System.out.printf("f(-.54719, -1.54719) : %.15f\n", mccormick(new double[]{-.54719, -1.54719}));
System.out.println();
state = psoInit(
new double[]{0.0, 0.0},
new double[]{Math.PI, Math.PI},
new Parameters(0.3, 3.0, 0.3),
1000
);
state = iterate(App::michalewicz, 30, state);
state.report("Michalewicz (2D)");
System.out.printf("f(2.20, 1.57) : %.15f\n", michalewicz(new double[]{2.20, 1.57}));
}
}</lang>
{{out}}
<pre>Test Function : McCormick
Iterations : 40
Global Best Position : [-0.5468738679864172, -1.547048532862534]
Global Best value : -1.913222827709136
f(-.54719, -1.54719) : -1.913222954882274
Test Function : Michalewicz (2D)
Iterations : 30
Global Best Position : [2.2029055320517994, 1.832848319327826]
Global Best value : -0.801303410098550
f(2.20, 1.57) : -0.801166387820286</pre>
=={{header|Kotlin}}==
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