cuckoo search, latin hypercube sampling

[imago.git] / pso.py

diff --git a/pso.py b/pso.py
index 9fdee2d..6d6fada 100644 (file)
--- a/pso.py
+++ b/pso.py
@@ -4,9 +4,14 @@ import random
 import multiprocessing
 from functools import partial
 
 import multiprocessing
 from functools import partial
 

-def particle(dimension, bound, func_d):
-    position = [2 * bound * random.random() - bound for _ in xrange(dimension)]
-    velocity = [2 * bound * random.random() - bound for _ in xrange(dimension)]
+import lhs
+
+def particle(dimension, bound, v_max, func_d, pos=None):
+    if not pos:
+        position = [2 * bound * random.random() - bound for _ in xrange(dimension)]
+    else:
+        position = pos
+    velocity = [2 * v_max * random.random() - v_max for _ in xrange(dimension)]

     value = func_d(*position)
     return value, position, velocity, value, position
 
     value = func_d(*position)
     return value, position, velocity, value, position
 


@@ -26,11 +31,13 @@ def move(particle, omega, phi_p, phi_g, v_max, global_best, func_d):
 
 def optimize(dimension, boundary, function_d, n_parts, n_turns):
     pool = multiprocessing.Pool(None)
 
 def optimize(dimension, boundary, function_d, n_parts, n_turns):
     pool = multiprocessing.Pool(None)

-    particles = [particle(dimension, boundary, function_d)
-                 for _ in xrange(n_parts)]
+    v_max = boundary
+    particles = [particle(dimension, boundary, v_max, function_d, pos)
+                 for pos in lhs.latin_hypercube(dimension, bound, n_parts)]

     gl_best = max(particles)
     for _ in xrange(n_turns):
     gl_best = max(particles)
     for _ in xrange(n_turns):

-        move_p = partial(move, omega=0.9, phi_p=0.9, phi_g=0.2, v_max=20.,
+        move_p = partial(move, 
+                         omega=0.98, phi_p=2.75, phi_g=3., v_max=v_max,

                          global_best=gl_best[1], func_d=function_d)
         particles = pool.map(move_p, particles)
         gl_best = max(max(particles), gl_best)
                          global_best=gl_best[1], func_d=function_d)
         particles = pool.map(move_p, particles)
         gl_best = max(max(particles), gl_best)