Particle swarm optimization: Difference between revisions
Rename Perl 6 -> Raku, alphabetize, minor clean-up
SqrtNegInf (talk | contribs) m (→{{header|Perl}}: oops, print results *correctly*) |
Thundergnat (talk | contribs) (Rename Perl 6 -> Raku, alphabetize, minor clean-up) |
||
Line 40:
</p>
<br><br>
=={{header|C sharp|C#}}==
{{trans|java}}
<lang csharp>using System;
namespace ParticleSwarmOptimization {
public struct Parameters {
public double omega, phip, phig;
public Parameters(double omega, double phip, double phig) : this() {
this.omega = omega;
this.phip = phip;
this.phig = phig;
}
}
public struct State {
public int iter;
public double[] gbpos;
public double gbval;
public double[] min;
public double[] max;
public Parameters parameters;
public double[][] pos;
public double[][] vel;
public double[][] bpos;
public double[] bval;
public int nParticles;
public int nDims;
public 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() {
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;
}
public void Report(string testfunc) {
Console.WriteLine("Test Function : {0}", testfunc);
Console.WriteLine("Iterations : {0}", iter);
Console.WriteLine("Global Best Position : {0}", string.Join(", ", gbpos));
Console.WriteLine("Global Best Value : {0}", gbval);
}
}
class Program {
public static State PsoInit(double[] min, double[] max, Parameters parameters, int nParticles) {
var nDims = min.Length;
double[][] pos = new double[nParticles][];
for (int i = 0; i < nParticles; i++) {
pos[i] = new double[min.Length];
min.CopyTo(pos[i], 0);
}
double[][] vel = new double[nParticles][];
for (int i = 0; i < nParticles; i++) {
vel[i] = new double[nDims];
}
double[][] bpos = new double[nParticles][];
for (int i = 0; i < nParticles; i++) {
bpos[i] = new double[min.Length];
min.CopyTo(bpos[i], 0);
}
double[] bval = new double[nParticles];
for (int i = 0; i < nParticles; i++) {
bval[i] = double.PositiveInfinity;
}
int iter = 0;
double[] gbpos = new double[nDims];
for (int i = 0; i < nDims; i++) {
gbpos[i] = double.PositiveInfinity;
}
double gbval = double.PositiveInfinity;
return new State(iter, gbpos, gbval, min, max, parameters, pos, vel, bpos, bval, nParticles, nDims);
}
static Random r = new Random();
public static State Pso(Func<double[], double> fn, State y) {
var 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] = new double[y.min.Length];
y.min.CopyTo(bpos[i], 0);
}
double[] bval = new double[y.nParticles];
double[] gbpos = new double[y.nDims];
double gbval = double.PositiveInfinity;
for (int j = 0; j < y.nParticles; j++) {
// evaluate
v[j] = fn.Invoke(y.pos[j]);
// update
if (v[j] < y.bval[j]) {
y.pos[j].CopyTo(bpos[j], 0);
bval[j] = v[j];
}
else {
y.bpos[j].CopyTo(bpos[j], 0);
bval[j] = y.bval[j];
}
if (bval[j] < gbval) {
gbval = bval[j];
bpos[j].CopyTo(gbpos, 0);
}
}
double rg = r.NextDouble();
double[][] pos = new double[y.nParticles][];
double[][] vel = new double[y.nParticles][];
for (int i = 0; i < y.nParticles; i++) {
pos[i] = new double[y.nDims];
vel[i] = new double[y.nDims];
}
for (int j = 0; j < y.nParticles; j++) {
// migrate
double rp = r.NextDouble();
bool ok = true;
for (int k = 0; k < y.nDims; k++) {
vel[j][k] = 0.0;
pos[j][k] = 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();
}
}
}
var iter = 1 + y.iter;
return new State(iter, gbpos, gbval, y.min, y.max, y.parameters, pos, vel, bpos, bval, y.nParticles, y.nDims);
}
public static State Iterate(Func<double[], double> fn, int n, State y) {
State r = y;
if (n == int.MaxValue) {
State old = y;
while (true) {
r = Pso(fn, r);
if (r.Equals(old)) break;
old = r;
}
}
else {
for (int i = 0; i < n; i++) {
r = Pso(fn, r);
}
}
return r;
}
public static double Mccormick(double[] x) {
var a = x[0];
var b = x[1];
return Math.Sin(a + b) + (a - b) * (a - b) + 1.0 + 2.5 * b - 1.5 * a;
}
public static double Michalewicz(double[] x) {
int m = 10;
int d = x.Length;
double sum = 0.0;
for (int i = 1; i < d; i++) {
var j = x[i - 1];
var k = Math.Sin(i * j * j / Math.PI);
sum += Math.Sin(j) * Math.Pow(k, 2.0 * m);
}
return -sum;
}
static void Main(string[] args) {
var 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(Mccormick, 40, state);
state.Report("McCormick");
Console.WriteLine("f(-.54719, -1.54719) : {0}", Mccormick(new double[] { -.54719, -1.54719 }));
Console.WriteLine();
state = PsoInit(
new double[] { -0.0, -0.0 },
new double[] { Math.PI, Math.PI },
new Parameters(0.3, 0.3, 0.3),
1000
);
state = Iterate(Michalewicz, 30, state);
state.Report("Michalewicz (2D)");
Console.WriteLine("f(2.20, 1.57) : {0}", Michalewicz(new double[] { 2.20, 1.57 }));
}
}
}</lang>
{{out}}
<pre>Test Function : McCormick
Iterations : 40
Global Best Position : -0.546850526417689, -1.54649614884518
Global Best Value : -1.91322235333426
f(-.54719, -1.54719) : -1.91322295488227
Test Function : Michalewicz (2D)
Iterations : 30
Global Best Position : 2.20290514143486, 2.20798457238775
Global Best Value : -0.801303410096221
f(2.20, 1.57) : -0.801166387820286</pre>
=={{header|C++}}==
Line 330 ⟶ 548:
Global Best Value : -0.801303
f(2.20, 1.57) : -0.801166</pre>
=={{header|D}}==
Line 981:
GlobalBestPosition: 2.20296 1.57083
GlobalBestValue: _1.8013</lang>
=={{header|Java}}==
Line 1,318 ⟶ 1,190:
Global Best value : -0.801303410098550
f(2.20, 1.57) : -0.801166387820286</pre>
=={{header|JavaScript}}==
Translation of [[Particle_Swarm_Optimization#J|J]].
<lang JavaScript>function pso_init(y) {
var nDims= y.min.length;
var pos=[], vel=[], bpos=[], bval=[];
for (var j= 0; j<y.nParticles; j++) {
pos[j]= bpos[j]= y.min;
var v= []; for (var k= 0; k<nDims; k++) v[k]= 0;
vel[j]= v;
bval[j]= Infinity}
return {
iter: 0,
gbpos: Infinity,
gbval: Infinity,
min: y.min,
max: y.max,
parameters: y.parameters,
pos: pos,
vel: vel,
bpos: bpos,
bval: bval,
nParticles: y.nParticles,
nDims: nDims}
}
function pso(fn, state) {
var y= state;
var p= y.parameters;
var val=[], bpos=[], bval=[], gbval= Infinity, gbpos=[];
for (var j= 0; j<y.nParticles; j++) {
// evaluate
val[j]= fn.apply(null, y.pos[j]);
// update
if (val[j] < y.bval[j]) {
bpos[j]= y.pos[j];
bval[j]= val[j];
} else {
bpos[j]= y.bpos[j];
bval[j]= y.bval[j]}
if (bval[j] < gbval) {
gbval= bval[j];
gbpos= bpos[j]}}
var rg= Math.random(), vel=[], pos=[];
for (var j= 0; j<y.nParticles; j++) {
// migrate
var rp= Math.random(), ok= true;
vel[j]= [];
pos[j]= [];
for (var k= 0; k < y.nDims; k++) {
vel[j][k]= p.omega*y.vel[j][k] + p.phip*rp*(bpos[j]-y.pos[j]) + p.phig*rg*(gbpos-y.pos[j]);
pos[j][k]= y.pos[j]+vel[j][k];
ok= ok && y.min[k]<pos[j][k] && y.max>pos[j][k];}
if (!ok)
for (var k= 0; k < y.nDims; k++)
pos[j][k]= y.min[k] + (y.max[k]-y.min[k])*Math.random()}
return {
iter: 1+y.iter,
gbpos: gbpos,
gbval: gbval,
min: y.min,
max: y.max,
parameters: y.parameters,
pos: pos,
vel: vel,
bpos: bpos,
bval: bval,
nParticles: y.nParticles,
nDims: y.nDims}
}
function display(text) {
if (document) {
var o= document.getElementById('o');
if (!o) {
o= document.createElement('pre');
o.id= 'o';
document.body.appendChild(o)}
o.innerHTML+= text+'\n';
window.scrollTo(0,document.body.scrollHeight);
}
if (console.log) console.log(text)
}
function reportState(state) {
var y= state;
display('');
display('Iteration: '+y.iter);
display('GlobalBestPosition: '+y.gbpos);
display('GlobalBestValue: '+y.gbval);
}
function repeat(fn, n, y) {
var r=y, old= y;
if (Infinity == n)
while ((r= fn(r)) != old) old= r;
else
for (var j= 0; j<n; j++) r= fn(r);
return r
}
function mccormick(a,b) {
return Math.sin(a+b) + Math.pow(a-b,2) + (1 + 2.5*b - 1.5*a)
}
state= pso_init({
min: [-1.5,-3], max:[4,4],
parameters: {omega: 0, phip: 0.6, phig: 0.3},
nParticles: 100});
reportState(state);
state= repeat(function(y){return pso(mccormick,y)}, 40, state);
reportState(state);</lang>
Example displayed result (random numbers are involved so there will be a bit of variance between repeated runs:
<lang Javascript>
Iteration: 0
GlobalBestPosition: Infinity
GlobalBestValue: Infinity
Iteration: 40
GlobalBestPosition: -0.5134004259016365,-1.5512442672625184
GlobalBestValue: -1.9114053788600853</lang>
=={{header|Julia}}==
Line 1,730:
Global best position: 2.20293 1.57080
Global best value: -1.80130</pre>
=={{header|Phix}}==
Line 2,253 ⟶ 2,143:
1.8558804696523914)
-6.432092623300999</pre>
=={{header|Raku}}==
(formerly Perl 6)
{{trans|J (via Javascript, Kotlin, D, Python)}}
<lang perl6>sub pso-init (%y) {
my $d = @(%y{'min'});
my $n = %y{'n'};
%y{'gbval'} = Inf;
%y{'gbpos'} = [Inf xx $d];
%y{'bval'} = [Inf xx $n];
%y{'bpos'} = [%y{'min'} xx $n];
%y{'pos'} = [%y{'min'} xx $n];
%y{'vel'} = [[0 xx $d] xx $n];
%y;
}
sub pso (&fn, %y) {
my %p = %y{'p'};
my $n = %y{'n'};
my $d = @(%y{'min'});
my @bpos = %y{'min'} xx $n;
my $gbval = Inf;
my $rand-g = rand;
my (@pos, @vel, @v, @gbpos, @bval);
for 0 ..^ $n -> \j {
@v[j] = &fn(%y{'pos'}[j]); # evaluate
# update
if @v[j] < %y{'bval'}[j] {
@bpos[j] = %y{'pos'}[j];
@bval[j] = @v[j];
} else {
@bpos[j] = %y{'bpos'}[j];
@bval[j] = %y{'bval'}[j];
}
if @bval[j] < $gbval {
$gbval = @bval[j];
@gbpos = |@bpos[j];
}
}
# migrate
for 0 ..^ $n -> \j {
my $rand-p = rand;
my $ok = True;
for 0 ..^ $d -> \k {
@vel[j;k] = %p{'ω'} × %y{'vel'}[j;k]
+ %p{'φ-p'} × $rand-p × (@bpos[j;k] - %y{'pos'}[j;k])
+ %p{'φ-g'} × $rand-g × (@gbpos[k] - %y{'pos'}[j;k]);
@pos[j;k] = %y{'pos'}[j;k] + @vel[j;k];
$ok = %y{'min'}[k] < @pos[j;k] < %y{'max'}[k] if $ok;
}
next if $ok;
@pos[j;$_] = %y{'min'}[$_] + (%y{'max'}[$_] - %y{'min'}[$_]) × rand for 0 ..^ $d;
}
return {gbpos => @gbpos, gbval => $gbval, bpos => @bpos, bval => @bval, pos => @pos, vel => @vel,
min => %y{'min'}, max => %y{'max'}, p=> %y{'p'}, n => $n}
}
sub report ($function-name, %state) {
say $function-name;
say '🌐 best position: ' ~ %state{'gbpos'}.fmt('%.5f');
say '🌐 best value: ' ~ %state{'gbval'}.fmt('%.5f');
say '';
}
sub mccormick (@x) {
my ($a,$b) = @x;
sin($a+$b) + ($a-$b)**2 + (1 + 2.5×$b - 1.5×$a)
}
my %state = pso-init( {
min => [-1.5, -3],
max => [4, 4],
n => 100,
p => {ω=> 0, φ-p=> 0.6, φ-g=> 0.3},
} );
%state = pso(&mccormick, %state) for 1 .. 40;
report 'McCormick', %state;
sub michalewicz (@x) {
my $sum;
my $m = 10;
for 1..@x -> $i {
my $j = @x[$i-1];
my $k = sin($i × $j**2/π);
$sum += sin($j) × $k**(2×$m)
}
-$sum
}
%state = pso-init( {
min => [0, 0],
max => [π, π],
n => 1000,
p => {ω=> 0.3, φ-p=> 0.3, φ-g=> 0.3},
} );
%state = pso(&michalewicz, %state) for 1 .. 30;
report 'Michalewicz', %state;</lang>
{{out}}
<pre>McCormick
🌐 best position: -0.54714 -1.54710
🌐 best value: -1.91322
Michalewicz
🌐 best position: 2.20291 1.57080
🌐 best value: -1.80130</pre>
=={{header|REXX}}==
| |||