octave_packages/ga-0.10.0/__ga_problem__.m

   1 ## Copyright (C) 2008 Luca Favatella <slackydeb@gmail.com>
   2 ##
   3 ## This program is free software; you can redistribute it and/or modify
   4 ## it under the terms of the GNU General Public License as published by
   5 ## the Free Software Foundation; either version 2 of the License, or
   6 ## (at your option) any later version.
   7 ##
   8 ## This program is distributed in the hope that it will be useful,
   9 ## but WITHOUT ANY WARRANTY; without even the implied warranty of
  10 ## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
  11 ## GNU General Public License for more details.
  12 ##
  13 ## You should have received a copy of the GNU General Public License
  14 ## along with this program; If not, see <http://www.gnu.org/licenses/>.
  15
  16 ## Author: Luca Favatella <slackydeb@gmail.com>
  17 ## Version: 5.9
  18
  19 function [x fval exitflag output population scores] = __ga_problem__ (problem)
  20
  21   ## first instruction
  22   state.StartTime = time ();
  23
  24   ## second instruction
  25   output = struct ("randstate", rand ("state"),
  26                    "randnstate", randn ("state"));
  27
  28   ## instructions not to be executed at each generation
  29   state.Population(1:problem.options.PopulationSize, 1:problem.nvars) = \
  30       __ga_initial_population__ (problem.nvars,
  31                                  problem.fitnessfcn,
  32                                  problem.options);
  33   state.Generation = 0;
  34   private_state = __ga_problem_private_state__ (problem.options);
  35   state.Selection = __ga_problem_state_selection__ (private_state,
  36                                                     problem.options);
  37
  38   ## instructions to be executed at each generation
  39   state = __ga_problem_update_state_at_each_generation__ (state, problem,
  40                                                           private_state);
  41
  42   NextPopulation = zeros (problem.options.PopulationSize, problem.nvars);
  43   while (! __ga_stop__ (problem, state)) ## fix a generation
  44
  45     ## elite
  46     if (private_state.ReproductionCount.elite > 0)
  47       [trash IndexSortedScores] = sort (state.Score);
  48       NextPopulation(state.Selection.elite, 1:problem.nvars) = \
  49           state.Population \
  50           (IndexSortedScores(1:private_state.ReproductionCount.elite, 1),
  51            1:problem.nvars);
  52     endif
  53
  54     ## selection for crossover and mutation
  55     parents(1, 1:private_state.nParents) = __ga_selectionfcn__ \
  56         (state.Expectation, private_state.nParents, problem.options);
  57
  58     ## crossover
  59     if (private_state.ReproductionCount.crossover > 0)
  60       NextPopulation(state.Selection.crossover, 1:problem.nvars) = \
  61           __ga_crossoverfcn__ \
  62           (parents(1, private_state.parentsSelection.crossover),
  63            problem.options, problem.nvars, problem.fitnessfcn,
  64            false, ## unused
  65            state.Population);
  66     endif
  67
  68     ## mutation
  69     if (private_state.ReproductionCount.mutation > 0)
  70       NextPopulation(state.Selection.mutation, 1:problem.nvars) = \
  71           __ga_mutationfcn__ \
  72           (parents(1, private_state.parentsSelection.mutation),
  73            problem.options, problem.nvars, problem.fitnessfcn,
  74            state, state.Score,
  75            state.Population);
  76     endif
  77
  78     ## update state structure
  79     state.Population(1:problem.options.PopulationSize,
  80                      1:problem.nvars) = NextPopulation;
  81     state.Generation++;
  82     state = __ga_problem_update_state_at_each_generation__ (state, problem,
  83                                                             private_state);
  84   endwhile
  85
  86   [x fval exitflag output population scores] = \
  87       __ga_problem_return_variables__ (state, problem);
  88 endfunction
  89
  90                                 #state structure fields
  91                                 #DONE state.Population
  92                                 #DONE state.Score
  93                                 #DONE state.Generation
  94                                 #DONE state.StartTime
  95                                 #state.StopFlag
  96                                 #DONE state.Selection
  97                                 #DONE state.Expectation
  98                                 #DONE state.Best
  99                                 #state.LastImprovement
 100                                 #state.LastImprovementTime
 101                                 #state.NonlinIneq
 102                                 #state.NonlinEq