3_MaTGA.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyMSOO.MFEA.model import MaTGA\n",
    "from pyMSOO.utils.Crossover import *\n",
    "from pyMSOO.utils.Mutation import *\n",
    "from pyMSOO.utils.Selection import *\n",
    "from pyMSOO.utils.DimensionAwareStrategy import *\n",
    "from pyMSOO.MFEA.benchmark.continous import *\n",
    "from pyMSOO.utils.MultiRun.RunMultiTime import * "
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Benchmark"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### CEC17"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# tasks, IndClass = CEC17_benchmark.get_2tasks_benchmark(1)\n",
    "# tasks, IndClass = WCCI22_benchmark.get_complex_benchmark(10)\n",
    "tasks, IndClass = CEC17_benchmark.get_10tasks_benchmark()\n",
    "# tasks, IndClass = WCCI22_benchmark.get_50tasks_benchmark(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Seed: 25 -- Time: 02m 13.09s  100 % [====================>]  Cost: 3.24E-06  2.22E-11  5.11E-17  0.00E+00  3.09E-04  1.27E-06  3.50E-07  7.83E-04  3.01E-14  2.01E-10  ,  \n",
      "END!\n"
     ]
    }
   ],
   "source": [
    "baseModel = MaTGA.model(seed = 25)\n",
    "baseModel.compile(\n",
    "    IndClass= IndClass,\n",
    "    tasks= tasks,\n",
    "    # crossover = KL_SBXCrossover(nc= 2, k= 100, conf_thres= 1),\n",
    "    crossover= SBX_Crossover(nc = 2),\n",
    "    mutation= PolynomialMutation(nm = 5),\n",
    "    selection= ElitismSelection(),\n",
    "    dimension_strategy=DaS_strategy(eta= 3)\n",
    ")\n",
    "solve = baseModel.fit(\n",
    "    nb_generations = 1000, rmp = 0.1, nb_inds_each_task= 100, \n",
    "    bound_pop= [0, 1], evaluate_initial_skillFactor= True\n",
    ")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Multitime model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "baseModel = MultiTimeModel(model= MaTGA)\n",
    "baseModel.compile(\n",
    "    IndClass= IndClass,\n",
    "    tasks= tasks,\n",
    "    crossover= SBX_Crossover(nc = 2),\n",
    "    mutation= PolynomialMutation(nm = 5),\n",
    "    selection= ElitismSelection(),\n",
    "    dimension_strategy=DaS_strategy(eta= 3)\n",
    ")\n",
    "baseModel.fit(\n",
    "    nb_generations = 1000, rmp = 0.1, nb_inds_each_task= 100, \n",
    "    bound_pop= [0, 1], evaluate_initial_skillFactor= True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Seed: 0 -- Time: 02m 15.02s  100 % [====================>]  Cost: 4.23E-05  8.45E-10  2.02E-11  3.00E-11  4.16E-03  8.40E-06  7.77E-04  1.63E-03  1.13E-05  3.11E+01  ,  \n",
      "END!\n",
      "Seed: 1 -- Time: 02m 29.28s  100 % [====================>]  Cost: 5.87E-06  1.39E-09  1.93E-12  2.89E-11  4.07E-04  1.03E-05  3.64E-04  1.47E-03  1.19E-05  3.95E+01  ,  \n",
      "END!\n",
      "Seed: 2 -- Time: 02m 17.29s  100 % [====================>]  Cost: 8.48E-06  1.56E-10  3.18E-11  1.93E-12  4.94E-04  3.65E-06  1.03E-03  1.53E-03  8.82E-06  4.08E+01  ,  \n",
      "END!\n",
      "Seed: 3 -- Time: 02m 21.81s  100 % [====================>]  Cost: 5.02E-06  8.77E-10  2.49E-12  1.67E-09  3.14E-04  8.87E-06  4.62E-04  1.76E-03  1.66E-05  4.66E+01  ,  \n",
      "END!\n",
      "Seed: 4 -- Time: 02m 6.43s  100 % [====================>]  Cost: 4.42E-06  1.52E-09  6.30E-12  8.28E-11  3.95E-04  1.05E-05  5.77E-04  8.31E-04  9.61E-06  4.13E+01  ,  \n",
      "END!\n",
      "Seed: 5 -- Time: 02m 17.94s  100 % [====================>]  Cost: 9.20E-07  3.17E-09  3.10E-12  5.29E-11  5.52E-05  1.72E-05  3.97E-04  3.47E-03  1.53E-05  4.35E+01  ,  \n",
      "END!\n",
      "Seed: 6 -- Time: 02m 4.91s  100 % [====================>]  Cost: 1.29E-05  1.51E-09  2.27E-11  4.36E-11  6.36E-04  1.14E-05  7.83E-04  1.44E-03  2.12E-05  3.87E+01  ,  \n",
      "END!\n",
      "Seed: 7 -- Time: 02m 5.35s  100 % [====================>]  Cost: 6.53E-05  3.02E-10  4.53E-12  7.75E-09  4.97E-03  4.83E-06  5.21E-04  1.28E-03  5.47E-06  3.59E+01  ,  \n",
      "END!\n",
      "Seed: 8 -- Time: 02m 3.24s  100 % [====================>]  Cost: 5.88E-06  7.23E-10  2.47E-11  2.35E-11  3.70E-04  6.90E-06  8.06E-04  1.22E-03  9.88E-03  4.15E+01  ,  \n",
      "END!\n",
      "Seed: 9 -- Time: 02m 7.23s  100 % [====================>]  Cost: 6.68E-06  1.80E-10  4.08E-11  4.04E-12  5.45E-04  3.52E-06  1.14E-03  1.67E-03  1.97E-05  4.00E+01  ,  \n",
      "END!\n",
      "Seed: 10 -- Time: 02m 17.08s  100 % [====================>]  Cost: 6.50E-05  1.72E-09  1.03E-11  1.74E-10  4.14E-03  1.18E-05  7.17E-04  1.85E-03  9.98E-06  4.60E+01  ,  \n",
      "END!\n",
      "Seed: 11 -- Time: 02m 4.60s  100 % [====================>]  Cost: 4.13E-06  4.66E-09  1.88E-12  1.01E-10  3.08E-04  1.84E-05  4.01E-04  1.27E-03  1.17E-05  3.78E+01  ,  \n",
      "END!\n",
      "Seed: 12 -- Time: 02m 12.54s  100 % [====================>]  Cost: 1.42E-06  1.40E-09  1.09E-11  1.84E-11  1.09E-04  1.05E-05  6.30E-04  1.62E-03  1.37E-05  3.61E+01  ,  \n",
      "END!\n",
      "Seed: 13 -- Time: 02m 24.27s  100 % [====================>]  Cost: 7.88E-06  3.50E-09  1.38E-12  6.13E-12  7.00E-04  1.61E-05  3.52E-04  1.33E-03  1.20E-05  3.28E+01  ,  \n",
      "END!\n",
      "Seed: 14 -- Time: 02m 24.07s  100 % [====================>]  Cost: 1.12E-05  4.99E-10  1.45E-12  4.45E-11  9.48E-04  6.15E-06  3.60E-04  1.50E-03  8.43E-06  4.61E+01  ,  \n",
      "END!\n",
      "Seed: 15 -- Time: 02m 9.65s  100 % [====================>]  Cost: 3.90E-05  5.43E-10  7.60E-12  2.01E-11  2.52E-03  6.34E-06  6.87E-04  1.59E-03  7.27E-06  4.41E+01  ,  \n",
      "END!\n",
      "Seed: 16 -- Time: 02m 14.13s  100 % [====================>]  Cost: 1.03E-05  2.14E-10  5.09E-11  8.98E-11  6.57E-04  4.11E-06  9.59E-04  8.28E-04  1.53E-05  4.40E+01  ,  \n",
      "END!\n",
      "Seed: 17 -- Time: 02m 5.07s  100 % [====================>]  Cost: 2.90E-05  2.23E-10  1.53E-11  1.86E-11  2.28E-03  4.17E-06  7.70E-04  1.24E-03  1.64E-05  3.00E+01  ,  \n",
      "END!\n",
      "Seed: 18 -- Time: 02m 7.35s  100 % [====================>]  Cost: 4.70E-06  2.02E-09  4.20E-12  2.98E-12  3.67E-04  1.24E-05  4.67E-04  9.71E-04  2.20E-05  4.74E+01  ,  \n",
      "END!\n",
      "Seed: 19 -- Time: 02m 11.94s  100 % [====================>]  Cost: 6.86E-07  1.32E-10  1.39E-12  1.23E-08  6.25E-05  3.75E-06  3.15E-04  1.91E-03  1.28E-05  3.14E+01  ,  \n",
      "END!\n",
      "Seed: 20 -- Time: 02m 4.88s  100 % [====================>]  Cost: 3.09E-06  3.68E-10  6.16E-12  3.55E-12  2.42E-04  5.35E-06  5.15E-04  1.00E-03  5.20E-06  3.98E+01  ,  \n",
      "END!\n",
      "Seed: 21 -- Time: 02m 2.68s  100 % [====================>]  Cost: 1.86E-06  4.71E-10  9.58E-12  4.39E-12  1.61E-04  6.10E-06  6.10E-04  1.18E+02  2.69E-05  4.43E+01  ,  \n",
      "END!\n",
      "Seed: 22 -- Time: 02m 7.84s  100 % [====================>]  Cost: 2.41E-05  5.78E-10  8.16E-11  2.21E-11  1.23E-03  6.77E-06  8.99E-04  1.36E-03  9.22E-06  2.93E+01  ,  \n",
      "END!\n",
      "Seed: 23 -- Time: 02m 7.78s  100 % [====================>]  Cost: 1.42E-06  8.24E-10  6.14E-13  5.88E-12  1.33E-04  8.19E-06  2.69E-04  9.33E-04  8.76E-06  3.25E+01  ,  \n",
      "END!\n",
      "Seed: 24 -- Time: 02m 0.22s  100 % [====================>]  Cost: 1.55E-05  2.52E-10  1.15E-11  6.77E-12  1.37E-03  4.45E-06  7.66E-04  1.08E-03  8.03E-06  2.49E+01  ,  \n",
      "END!\n",
      "Seed: 25 -- Time: 02m 3.32s  100 % [====================>]  Cost: 5.18E-06  1.69E-10  1.92E-12  1.29E-11  4.67E-04  3.75E-06  3.80E-04  1.32E-03  7.41E-03  3.74E+01  ,  \n",
      "END!\n",
      "Seed: 26 -- Time: 02m 4.76s  100 % [====================>]  Cost: 2.63E-05  1.53E-10  2.13E-12  1.31E-11  1.59E-03  3.35E-06  3.77E-04  1.88E-03  1.52E-05  4.46E+01  ,  \n",
      "END!\n",
      "Seed: 27 -- Time: 02m 2.95s  100 % [====================>]  Cost: 8.09E-06  9.33E-09  1.32E-13  3.93E-11  6.60E-04  2.79E-05  1.42E-04  1.19E-03  2.24E-05  2.01E+01  ,  \n",
      "END!\n",
      "Seed: 28 -- Time: 02m 6.28s  100 % [====================>]  Cost: 1.17E-04  1.19E-09  6.97E-13  1.18E-11  1.11E-02  9.55E-06  2.64E-04  1.20E-03  9.55E-06  4.35E+01  ,  \n",
      "END!\n",
      "Seed: 29 -- Time: 02m 4.97s  100 % [====================>]  Cost: 5.76E-06  5.73E-10  1.28E-10  2.91E-11  3.24E-04  6.68E-06  1.70E-03  1.08E-03  1.79E-05  4.12E+01  ,  \n",
      "END!\n",
      "DONE!\n",
      "Done\n"
     ]
    }
   ],
   "source": [
    "baseModel.run(\n",
    "    nb_run= 30,\n",
    "    save_path= './RESULTS/MaTGA_cec17.mso'\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Error when create object DictType. Using Temp class instead\n",
      "Error when create object UnicodeType. Using Temp class instead\n",
      "Error when create object Float. Using Temp class instead\n",
      "Error when create object Tuple. Using Temp class instead\n",
      "Error when create object UnionType. Using Temp class instead\n",
      "Error while create instance model for <class 'pyMSOO.utils.EA.Population'>. Using Temp class instead\n",
      "Error while create instance model for <class 'pyMSOO.utils.EA.SubPopulation'>. Using Temp class instead\n"
     ]
    }
   ],
   "source": [
    "from pyMSOO.utils.LoadSaveModel.LoadModel import loadModel\n",
    "\n",
    "baseModel = loadModel('./RESULTS/MaTGA_cec17.mso', ls_tasks= tasks, set_attribute= True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "baseModel.render_history()\n",
    "print()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "MFEA",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.16"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "4a3c9e26fdc3510968d8c8d0068758f6f26fdb383cb924cc52c2f44397c2f98e"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}