This is my first PoC of the Travelling Salesman Problem on PSP, since I’ve installed the Pyevolve on the Sony PSP,  I can optimize any problem while using the graphical interface of PSP (in that problem I’m using the 2D functions to plot the cities and the path) to show results in real-time. Here is the video, the quality is very low, I’ve used my cellphone 🙂

Here is the source code I’ve used, the Pyevolve version of this example is the development version r166, which in the future will be the 0.6 final release (I’m working on many new features yet, so it will take time to release), however, this PoC should work on 0.5 release too:

import psp2d, pspos

WHITE_COLOR = psp2d.Color(255,255,255)
CLEAR_COLOR = psp2d.Color(0,0,0,255)
RED_COLOR   = psp2d.Color(255, 0, 0)

cm     = []
coords = []
CITIES = 20

pspos.setclocks(333,166)
psp_scr  = psp2d.Screen()
psp_font = psp2d.Font('font.png')
psp_scr.clear(CLEAR_COLOR)
psp_font.drawText(psp_scr, 0, 5, "Loading Pyevolve modules...")
psp_scr.swap()

from pyevolve import G1DList
from pyevolve import GSimpleGA
from pyevolve import GAllele
from pyevolve import Mutators
from pyevolve import Crossovers
from pyevolve import Consts

from random import shuffle as rand_shuffle, randint as rand_randint
from math import sqrt

def cartesian_matrix(coords):
   """ A distance matrix """
   matrix={}
   for i,(x1,y1) in enumerate(coords):
      for j,(x2,y2) in enumerate(coords):
         dx, dy = x1-x2, y1-y2
         dist=sqrt(dx*dx + dy*dy)
         matrix[i,j] = dist
   return matrix

def tour_length(matrix, tour):
   """ Returns the total length of the tour """
   total = 0
   for i in range(CITIES):
      j      = (i+1)%CITIES
      total += matrix[tour[i], tour[j]]
   return total

def write_tour_to_img(coords, tour):
   """ The function to plot the graph """
   psp_scr.clear(CLEAR_COLOR)
   for i in range(CITIES):
      j      = (i+1)%CITIES
      city_i = tour[i]
      city_j = tour[j]
      x1, y1 = coords[city_i]
      x2, y2 = coords[city_j]
      psp_scr.drawLine(int(x1), int(y1), int(x2), int(y2), WHITE_COLOR)
      psp_font.drawText(psp_scr, int(x1)+7, int(y1)-5, str(i))
      psp_scr.fillRect(int(x1), int(y1), 6, 6, RED_COLOR)

   psp_scr.swap()

def G1DListTSPInitializator(genome, **args):
   """ The initializator for the TSP """
   lst = [i for i in xrange(genome.getListSize())]
   rand_shuffle(lst)
   genome.genomeList = lst

def evolve_callback(ga_engine):
   """ Callback called every generation by Pyevolve """
   write_tour_to_img(coords, ga_engine.bestIndividual())
   return False

def main_run():
   global cm, coords

   width, height = psp_scr.size
   coords = [(rand_randint(0, width),rand_randint(0, height))
                 for i in xrange(CITIES)]
   cm     = cartesian_matrix(coords)

   setOfAlleles = GAllele.GAlleles(homogeneous=True)
   range_allele = GAllele.GAlleleRange(0, len(coords)-1)
   setOfAlleles.add(range_allele)

   genome = G1DList.G1DList(len(coords))
   genome.setParams(allele=setOfAlleles)

   genome.evaluator.set(lambda chromosome: tour_length(cm, chromosome))
   genome.mutator.set(Mutators.G1DListMutatorSwap)
   genome.crossover.set(Crossovers.G1DListCrossoverOX)
   genome.initializator.set(G1DListTSPInitializator)

   ga = GSimpleGA.GSimpleGA(genome)
   ga.setMinimax(Consts.minimaxType["minimize"])
   ga.setGenerations(300)
   ga.setPopulationSize(200)
   ga.setCrossoverRate(1.0)
   ga.setMutationRate(0.1)
   ga.stepCallback.set(evolve_callback)

   ga.evolve()

if __name__ == "__main__":
   main_run()