geatpy_nb.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import benchmark_funs as bf\n",
    "bf_functions = bf.benchmark_functions\n",
    "lb = [f.lb  for f in bf_functions for j in range(f.dimension)]\n",
    "ub = [f.ub  for f in bf_functions for j in range(f.dimension)]\n",
    "dims = [f.dimension for f in bf_functions]\n",
    "dim = sum(dims)\n",
    "varTypes = [0]*dim\n",
    "budget = 10000 * dim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/yecm/anaconda3/envs/torch2.0/lib/python3.9/site-packages/numpy/core/_methods.py:239: RuntimeWarning: overflow encountered in multiply\n",
      "  x = um.multiply(x, x, out=x)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "==================================================================================\n",
      "gen|  eval  |    f_opt    |    f_max    |    f_avg    |    f_min    |    f_std    \n",
      "----------------------------------------------------------------------------------\n",
      " 0 |  100   |60525634000.0|2.4879573e+22|3.0126383e+20|60525634000.0|     inf     \n",
      " 1 |  200   |32248898000.0|1.4322161e+16|1625144200000000.0|32248898000.0|3068359800000000.0\n",
      " 2 |  300   | 2818683000.0|186517860000000.0|23181694000000.0| 2818683000.0|39727307000000.0\n",
      " 3 |  400   | 2719058400.0|1856778000000.0|798486950000.0| 2719058400.0|753656140000.0\n",
      " 4 |  500   | 1375404300.0|361520270000.0|78183100000.0| 1375404300.0|113784316000.0\n",
      " 5 |  600   | 289355650.0 |27906724000.0| 5957402600.0| 289355650.0 | 5727411000.0\n",
      " 6 |  700   | 289355650.0 | 3194077200.0| 2538205200.0| 289355650.0 | 616637440.0 \n",
      " 7 |  800   | 289355650.0 | 2723399200.0| 2080431100.0| 289355650.0 | 819901800.0 \n",
      " 8 |  900   | 289349950.0 | 2371107000.0| 1117834400.0| 289349950.0 | 541030000.0 \n",
      " 9 |  1000  | 239992420.0 | 835044500.0 | 555508800.0 | 239992420.0 | 156415760.0 \n",
      " 10|  1100  | 239992420.0 | 504210080.0 | 387591460.0 | 239992420.0 |  88527656.0 \n",
      " 11|  1200  | 239272050.0 | 334032300.0 | 284713820.0 | 239272050.0 |  23751626.0 \n",
      " 12|  1300  | 221660900.0 | 289354560.0 | 260005820.0 | 221660900.0 |  22147158.0 \n",
      " 13|  1400  | 221660900.0 | 240042270.0 | 239596770.0 | 221660900.0 |  1903223.4  \n",
      " 14|  1500  | 215110600.0 | 239992020.0 | 238053970.0 | 215110600.0 |  4874368.0  \n",
      " 15|  1600  | 215110600.0 | 239279790.0 | 233438500.0 | 215110600.0 |  8281943.5  \n",
      " 16|  1700  | 214465550.0 | 235961470.0 | 223297680.0 | 214465550.0 |  6249963.0  \n",
      " 17|  1800  | 207380560.0 | 221660880.0 | 218650530.0 | 207380560.0 |  3231771.5  \n",
      " 18|  1900  | 196188770.0 | 220957780.0 | 214602670.0 | 196188770.0 |  2860903.8  \n",
      " 19|  2000  | 196188770.0 | 215097780.0 | 212573390.0 | 196188770.0 |  4417753.5  \n",
      " 20|  2100  | 196188770.0 | 214437180.0 | 209119330.0 | 196188770.0 |  5615908.5  \n",
      " 21|  2200  | 196188770.0 | 207380580.0 | 202625920.0 | 196188770.0 |  4077598.0  \n",
      " 22|  2300  | 179468510.0 | 200700670.0 | 197339040.0 | 179468510.0 |  4094136.5  \n",
      " 23|  2400  | 165766400.0 | 197662910.0 | 193052480.0 | 165766400.0 |  6998236.5  \n",
      " 24|  2500  | 165761860.0 | 196227680.0 | 188208080.0 | 165761860.0 |  9237480.0  \n",
      " 25|  2600  | 165346510.0 | 183972590.0 | 177554850.0 | 165346510.0 |  6559370.5  \n",
      " 26|  2700  | 163303890.0 | 179468510.0 | 170893100.0 | 163303890.0 |  6403185.0  \n",
      " 27|  2800  | 163303710.0 | 165788580.0 | 165705140.0 | 163303710.0 |   353468.1  \n",
      " 28|  2900  | 163289100.0 | 165766380.0 | 165563440.0 | 163289100.0 |   586983.7  \n",
      " 29|  3000  | 110162570.0 | 165752590.0 | 164506050.0 | 110162570.0 |  5555329.0  \n",
      " 30|  3100  | 109927390.0 | 165345460.0 | 163039540.0 | 109927390.0 |  7645880.5  \n",
      " 31|  3200  | 107699030.0 | 163303710.0 | 160492340.0 | 107699030.0 |  11701791.0 \n",
      " 32|  3300  | 107693144.0 | 163290400.0 | 157300930.0 | 107693144.0 |  16203924.0 \n",
      " 33|  3400  | 107687350.0 | 163161950.0 | 145024210.0 | 107687350.0 |  24316610.0 \n",
      " 34|  3500  | 107679544.0 | 161183520.0 | 117634170.0 | 107679544.0 |  18819482.0 \n",
      " 35|  3600  | 107324570.0 | 107823660.0 | 107690776.0 | 107324570.0 |  60265.242  \n",
      " 36|  3700  | 104543090.0 | 107696450.0 | 107625220.0 | 104543090.0 |  322884.16  \n",
      " 37|  3800  | 104531016.0 | 107687000.0 | 107505950.0 | 104531016.0 |  452551.97  \n",
      " 38|  3900  | 104530250.0 | 107570320.0 | 107157310.0 | 104530250.0 |  782107.75  \n",
      " 39|  4000  | 104168650.0 | 107330670.0 | 106670260.0 | 104168650.0 |  1117101.6  \n",
      " 40|  4100  |  99264390.0 | 107218940.0 | 105391240.0 |  99264390.0 |  1380131.6  \n",
      " 41|  4200  |  99262080.0 | 104532460.0 | 104223810.0 |  99262080.0 |  1027839.0  \n",
      " 42|  4300  |  99259400.0 | 104527016.0 | 103337760.0 |  99259400.0 |  1853915.1  \n",
      " 43|  4400  |  97915930.0 | 104162110.0 | 101801944.0 |  97915930.0 |  2334581.2  \n",
      " 44|  4500  |  97910920.0 |  99264390.0 |  99162840.0 |  97910920.0 |   330523.0  \n",
      " 45|  4600  |  97501510.0 |  99262100.0 |  98951270.0 |  97501510.0 |  540228.06  \n",
      " 46|  4700  |  97501380.0 |  99257370.0 |  98294990.0 |  97501380.0 |   551301.3  \n",
      " 47|  4800  |  97501380.0 |  97915384.0 |  97838670.0 |  97501380.0 |  157510.62  \n",
      " 48|  4900  |  94918136.0 |  97911690.0 |  97677050.0 |  94918136.0 |  342430.84  \n",
      " 49|  5000  |  92809330.0 |  97503790.0 |  97376990.0 |  92809330.0 |   636297.8  \n",
      " 50|  5100  |  92808640.0 |  97501500.0 |  97027980.0 |  92808640.0 |  1179423.0  \n",
      " 51|  5200  |  92806510.0 |  97498740.0 |  96099660.0 |  92806510.0 |  1712624.6  \n",
      " 52|  5300  |  90369016.0 |  94920136.0 |  94051780.0 |  90369016.0 |  1078622.6  \n",
      " 53|  5400  |  69137940.0 |  94520424.0 |  92527870.0 |  69137940.0 |  2490811.2  \n",
      " 54|  5500  |  69137930.0 |  92808910.0 |  91849820.0 |  69137930.0 |  3389172.0  \n",
      " 55|  5600  |  69128120.0 |  92805650.0 |  89191860.0 |  69128120.0 |  6417361.5  \n",
      " 56|  5700  |  69127430.0 |  90368730.0 |  84677470.0 |  69127430.0 |  9010610.0  \n",
      " 57|  5800  |  47104612.0 |  89807580.0 |  75097160.0 |  47104612.0 |  9390146.0  \n",
      " 58|  5900  |  47104596.0 |  69137930.0 |  68228540.0 |  47104596.0 |  3841521.5  \n",
      " 59|  6000  |  47104590.0 |  69128140.0 |  66851052.0 |  47104590.0 |  5661312.5  \n",
      " 60|  6100  |  46768620.0 |  69097180.0 |  61961468.0 |  46768620.0 |  8628478.0  \n",
      " 61|  6200  |  46725384.0 |  64580576.0 |  53788210.0 |  46725384.0 |  8129378.0  \n",
      " 62|  6300  |  45927624.0 |  47113896.0 |  47063756.0 |  45927624.0 |  148098.92  \n",
      " 63|  6400  |  39536124.0 |  47104590.0 |  46907904.0 |  39536124.0 |   782719.0  \n",
      " 64|  6500  |  39535820.0 |  47076424.0 |  46652692.0 |  39535820.0 |  1065166.5  \n",
      " 65|  6600  |  39190572.0 |  46768600.0 |  46072380.0 |  39190572.0 |  1838921.8  \n",
      " 66|  6700  |  35775730.0 |  46758260.0 |  44443780.0 |  35775730.0 |  2970340.5  \n",
      " 67|  6800  |  35775730.0 |  45926668.0 |  41503456.0 |  35775730.0 |  3242734.8  \n",
      " 68|  6900  |  35775730.0 |  39536132.0 |  38882920.0 |  35775730.0 |   969276.1  \n",
      " 69|  7000  |  35775670.0 |  39190270.0 |  38101830.0 |  35775670.0 |  1082531.0  \n",
      " 70|  7100  |  26611140.0 |  37594080.0 |  36769300.0 |  26611140.0 |  1496109.2  \n",
      " 71|  7200  |  26610434.0 |  36513160.0 |  35371252.0 |  26610434.0 |  2370836.0  \n",
      " 72|  7300  |  25292916.0 |  35781736.0 |  34090584.0 |  25292916.0 |  3316133.8  \n",
      " 73|  7400  |  24947124.0 |  35775496.0 |  31409364.0 |  24947124.0 |  4084455.2  \n",
      " 74|  7500  |  24947118.0 |  28812092.0 |  27077876.0 |  24947118.0 |  1060768.6  \n",
      " 75|  7600  |  24947016.0 |  26611094.0 |  26296018.0 |  24947016.0 |   482999.3  \n",
      " 76|  7700  |  24946820.0 |  26274308.0 |  25883188.0 |  24946820.0 |  513220.88  \n",
      " 77|  7800  |  24826722.0 |  26144766.0 |  25317254.0 |  24826722.0 |  401891.38  \n",
      " 78|  7900  |  23581518.0 |  25290828.0 |  24962988.0 |  23581518.0 |   176329.9  \n",
      " 79|  8000  |  23581518.0 |  24947094.0 |  24906136.0 |  23581518.0 |  194406.05  \n",
      " 80|  8100  |  23580920.0 |  24946618.0 |  24852526.0 |  23580920.0 |  271182.47  \n",
      " 81|  8200  |  23577216.0 |  24940142.0 |  24646150.0 |  23577216.0 |   456581.4  \n",
      " 82|  8300  |  23323742.0 |  24826722.0 |  24275514.0 |  23323742.0 |  520958.47  \n",
      " 83|  8400  |  23098812.0 |  24327722.0 |  23666978.0 |  23098812.0 |   272522.3  \n",
      " 84|  8500  |  23098242.0 |  23580962.0 |  23514178.0 |  23098242.0 |  114338.65  \n",
      " 85|  8600  |  23072106.0 |  23576972.0 |  23403568.0 |  23072106.0 |  133492.52  \n",
      " 86|  8700  |  22857950.0 |  23323716.0 |  23262814.0 |  22857950.0 |   99515.77  \n",
      " 87|  8800  |  22857428.0 |  23306818.0 |  23157330.0 |  22857428.0 |  107194.02  \n",
      " 88|  8900  |  22857428.0 |  23099898.0 |  23063956.0 |  22857428.0 |   68702.2   \n",
      " 89|  9000  |  22815094.0 |  23072116.0 |  23010020.0 |  22815094.0 |  92658.375  \n",
      " 90|  9100  |  22813094.0 |  23067418.0 |  22903544.0 |  22813094.0 |   81352.17  \n",
      " 91|  9200  |  22761804.0 |  22857900.0 |  22848258.0 |  22761804.0 |  17519.008  \n",
      " 92|  9300  |  22761558.0 |  22857222.0 |  22835208.0 |  22761558.0 |  21913.494  \n",
      " 93|  9400  |  22176550.0 |  22830406.0 |  22805044.0 |  22176550.0 |   65390.99  \n",
      " 94|  9500  |  22160524.0 |  22813810.0 |  22771118.0 |  22160524.0 |  124211.44  \n",
      " 95|  9600  |  22160524.0 |  22801838.0 |  22700580.0 |  22160524.0 |  186194.61  \n",
      " 96|  9700  |  22108048.0 |  22761672.0 |  22556532.0 |  22108048.0 |  272260.72  \n",
      " 97|  9800  |  22108048.0 |  22752658.0 |  22290340.0 |  22108048.0 |  213090.75  \n",
      " 98|  9900  |  20154338.0 |  22176548.0 |  22138100.0 |  20154338.0 |  200626.75  \n",
      " 99| 10000  |  20154338.0 |  22160528.0 |  22101584.0 |  20154338.0 |  279715.22  \n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Execution time: 10.031137466430664 s\n",
      "Evaluation number: 10000\n",
      "The best objective value is: 20154338.0\n",
      "The best variables are: \n",
      "-7.550305500626564\t-65.9823814406991\t-39.884879253804684\t-42.492979764938354\t-38.29743592068553\t-12.457355484366417\t-11.497980821877718\t-49.064326751977205\t-4.026385303586721\t1.092451624572277\t66.98932722210884\t-21.5338833630085\t53.926024585962296\t-8.662240020930767\t-13.867021538317204\t-13.42426398769021\t-69.85529931262136\t21.532605681568384\t7.964284997433424\t35.9690603800118\t-74.12781035527587\t-16.505225095897913\t-60.49910681322217\t-81.10364833846688\t-78.02583603188396\t-79.02724863961339\t-91.61705235019326\t-13.061759434640408\t-81.44010584801435\t67.38260397687554\t0.21835695952177048\t2.26281744427979\t-16.867731856182218\t-3.371853595599532\t-7.5325702875852585\t2.834608554840088\t-4.500294579192996\t-1.5110759250819683\t2.972478624433279\t-12.236998714506626\t-2.7371045015752316\t-7.114701373502612\t6.309396307915449\t-6.974906958639622\t-10.974738886579871\t-2.022817935794592\t12.573336521163583\t6.191621627658606\t-6.812978982925415\t7.461706520989537\t-12.988363383337855\t1.8861206900328398\t-4.988087173551321\t-3.0140109546482563\t6.500338688492775\t7.68197787925601\t-2.8357893135398626\t1.8146274983882904\t0.08682584390044212\t24.412153316661716\t93.97479286417365\t62.63274913653731\t100.0\t-63.032229989767075\t-48.60676284879446\t-36.192189157009125\t46.4166559278965\t36.39225522056222\t-62.225011829286814\t6.324918009340763\t95.60206886380911\t-71.29986537620425\t82.4135527946055\t-39.61661010980606\t-7.055658753961325\t-60.425013676285744\t-90.10933646932244\t34.85584445297718\t60.256449691951275\t-6.569457147270441\t-15.267604310065508\t-82.98316327854991\t96.59261181950569\t18.10391265898943\t6.9701336324214935\t18.65103244781494\t43.710505589842796\t91.2789466790855\t74.69979077577591\t-24.359449930489063\t0.2898824834823608\t0.8790346705913545\t-0.7901017701625824\t-1.1319829893112183\t-1.2077803146839143\t-0.1322683334350585\t-0.3152430093288422\t0.6663553237915039\t-0.9464474666118622\t0.16827439785003656\t-0.5326857256889344\t-1.0027409851551057\t0.5356361210346221\t-0.7577922487258911\t-0.22983359336853026\t-0.8346738696098328\t-0.25123242378234867\t-0.023233100175857446\t0.8914711737632753\t-0.7592467415332794\t1.1726778483390807\t-0.5839688086509705\t-0.5414312314987183\t1.1303132796287536\t0.9277612733840941\t0.8277864789962768\t-0.191576063632965\t0.6905055141448975\t0.07608375430107106\t-0.2360461831092835\t459.1620257124305\t-357.0444383658469\t-248.83262161165476\t-349.2273376323283\t-49.226246774196625\t-220.62180703505874\t98.86120399460196\t77.6319527067244\t-460.3258050046861\t229.14753342047334\t-356.63490695878863\t-168.4061661362648\t337.45946548879147\t-204.4848594814539\t-432.01536126434803\t261.6136306896806\t87.26950082927942\t-465.4659377411008\t-500.0\t-407.80846402049065\t-44.4576246663928\t389.81280056759715\t361.4109973423183\t143.15361250191927\t-403.56766944751143\t-325.0353164039552\t-425.491763278842\t-60.167089104652405\t452.5192519649863\t314.05083229765296\t15.869056761264801\t24.716631203889847\t-30.916680723428726\t24.615870416164398\t-14.747412770986557\t18.50560572743416\t-20.346600890159607\t7.718133389949799\t-15.798146814107895\t18.581571489572525\t9.869811743497849\t-24.798956483602524\t29.735646605491638\t-12.46295639872551\t-16.687967658042908\t1.440600037574768\t-30.096707940101624\t-3.0767826437950134\t14.084181278944016\t9.778531581163406\t-2.4265312552452087\t30.277076214551926\t-14.897105932235718\t-11.752961814403534\t11.954678028821945\t-6.435119688510895\t8.182923078536987\t-26.281685411930084\t-18.616604059934616\t-11.05214747786522\t3.082592859864235\t1.4803192485123873\t1.1093437485396862\t0.21416091360151768\t0.2829534746706486\t-1.7215109523385763\t0.11312458664178848\t0.6155531294643879\t1.3191297929733992\t0.05535806529223919\t-3.577724853530526\t-5.596554027870297\t2.3056460171937943\t0.21460716612637043\t5.747995628044009\t0.23224725387990475\t-1.7724196705967188\t-5.5168255884200335\t-2.5805890187621117\t5.17841980792582\t3.933689948171377\t2.1288087498396635\t-2.2801187355071306\t0.013387473300099373\t-5.537443254143\t8.42735338024795\t1.0797628853470087\t-4.546363800764084\t-8.452549101784825\t0.21238443441689014\t1.5837576612830162\t-6.089726202189922\t1.6170646902173758\t-2.665149327367544\t2.1363645246147587\t1.1961882737687037\t\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import geatpy as ea\n",
    "import torch\n",
    "# 构建问题\n",
    "@ea.Problem.single\n",
    "def evalVars(Vars):  # 定义目标函数（含约束）\n",
    "    S1 = 0\n",
    "    current_dim_start = 0\n",
    "    for f in bf_functions:\n",
    "        S1+=f(torch.Tensor(Vars[current_dim_start:current_dim_start+f.dimension]).reshape(1, -1))\n",
    "        current_dim_start += f.dimension\n",
    "    return S1, 0\n",
    "\n",
    "problem = ea.Problem(name='演化计算求解',\n",
    "                     M=1,  # 目标维数\n",
    "                     maxormins=[1],  # 目标最小最大化标记列表，1：最小化该目标；-1：最大化该目标\n",
    "                     Dim=dim,  # 决策变量维数\n",
    "                     varTypes=varTypes,  # 决策变量的类型列表，0：实数；1：整数\n",
    "                     lb=lb,  # 决策变量下界\n",
    "                     ub=ub,  # 决策变量上界\n",
    "                     evalVars=evalVars)\n",
    "NIND = 100\n",
    "MAXGEN = budget//(NIND*dim)\n",
    "# 构建算法\n",
    "algorithm = ea.soea_SEGA_templet(problem,\n",
    "                                 ea.Population(Encoding='RI', NIND=NIND),\n",
    "                                #  MAXGEN=80,  # 最大进化代数。\n",
    "                                 MAXGEN=MAXGEN,  # 最大进化代数。\n",
    "                                 logTras=1,  # 表示每隔多少代记录一次日志信息，0表示不记录。\n",
    "                                #  trappedValue=1e-8,  # 单目标优化陷入停滞的判断阈值。\n",
    "                                 trappedValue=1e-6,  # 单目标优化陷入停滞的判断阈值。\n",
    "                                 maxTrappedCount=100)  # 进化停滞计数器最大上限值。\n",
    "                                #  maxTrappedCount=10)  # 进化停滞计数器最大上限值。\n",
    "# 求解\n",
    "res = ea.optimize(algorithm, \n",
    "    seed=128, verbose=True, drawing=1, outputMsg=True, drawLog=True, saveFlag=True, dirName='runs/geatpy')"
   ]
  }
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