使用deap进行遗传算法并发优化实践

一时失言乱红尘 2022-12-14 13:57 187阅读 0赞

直接上代码

# -*- coding: utf-8 -*-
    import array
    import random
    import json
    import numpy
    import numpy as np
    import pandas as pd
    import  os
    from deap import algorithms,base,creator,tools
    import multiprocessing
    
    POP_SIZE = 200
    #生成模拟数据
    df=[int((800 -500) * np.random.random_sample()+ 500) for h in range(1800)]
    IND_SIZE=1800
    
    """
    假设有这么一个应用场景：
    高一新生对其所有的新生进行分班，分为30个班
    要求每个班的人数和分数（中考成绩）总和尽可能相等，每个班60个人
    再把问题进行简化，新生总人数是60的倍数，总人数为1800人
    假设学生的学号是1-1800
    """
    
    creator.create("FitnessMin", base.Fitness, weights=(-1.0,))
    creator.create("Individual", array.array, typecode='i', fitness=creator.FitnessMin)
    toolbox = base.Toolbox()
    # Attribute generator
    toolbox.register("indices", random.sample, range(IND_SIZE), IND_SIZE)
    # Structure initializers
    toolbox.register("individual", tools.initIterate, creator.Individual, toolbox.indices)
    toolbox.register("population", tools.initRepeat, list, toolbox.individual)
    
    def translateDNA(DNA, df):
        #print(DNA)
        score_p = np.empty_like(DNA, dtype=np.int64)
        for i, d in enumerate(DNA):       
            score_p[i]=df[d]
        return score_p
    
    def evalTSP(individual):
        score_p=translateDNA(individual, df)
        sum_score=[0 for h in range(30)]
        for index_c in range(30):#总班级人数
             sum_score[index_c]=np.sum(score_p[60*index_c:60*(index_c+1)])
        loss=np.std(sum_score)
        return loss,
    
    toolbox.register("mate", tools.cxPartialyMatched)
    toolbox.register("mutate", tools.mutShuffleIndexes, indpb=0.05)
    toolbox.register("select", tools.selTournament, tournsize=3)
    toolbox.register("evaluate", evalTSP)
    
    if __name__ == "__main__":
    
        random.seed(234)
        # 开启8个进程进行并发计算
        pool = multiprocessing.Pool(processes=8)
        toolbox.register("map", pool.map)
    
        pop = toolbox.population(n=POP_SIZE)
        hof = tools.HallOfFame(1)
        ##将优化的结果进行统计
        stats = tools.Statistics(lambda ind: ind.fitness.values)
        stats.register("avg", numpy.mean)
        stats.register("std", numpy.std)
        stats.register("min", numpy.min)
        stats.register("max", numpy.max)
        pop, logbook=algorithms.eaSimple(pop, toolbox, 0.7, 0.1, 200, stats=stats, halloffame=hof)
        pool.close()
        #将优化的结果写入本地文件
        #os.chdir("data")
        #f=open("result.txt","w")
        #print(hof,file=f)

运行结果:

gen	nevals	avg    	std    	min    	max    
    0  	200   	663.038	90.2416	363.649	863.209
    1  	156   	641.244	81.6451	446.055	860.084
    2  	145   	621.187	81.9976	409.38 	821.071
    3  	147   	625.44 	95.0025	446.055	836.111
    4  	139   	624.654	94.4089	446.055	874.641
    5  	137   	611.439	90.5689	435.377	850.604
    6  	140   	603.547	94.0976	436.471	939.92 
    7  	139   	596.746	92.2356	417.962	862.49 
    8  	137   	608.979	96.9298	425.851	857.976
    9  	152   	618.447	93.0757	394.298	906.374
    10 	147   	617.68 	92.8426	391.621	886.907
    11 	163   	626.885	89.9386	420.405	853.935
    12 	155   	620.154	80.2981	456.917	873.394
    13 	149   	624.371	78.9701	430.235	860.649
    14 	147   	619.778	87.3665	375.372	905.794
    15 	151   	628.543	87.992 	432.697	863.73 
    16 	129   	612.099	84.33  	455.366	888.036
    17 	153   	620.685	88.6167	455.366	873.521
    18 	151   	616.773	92.4059	445.476	899.183
    19 	144   	601.46 	87.0975	439.18 	839.135
    20 	153   	622.978	96.2228	439.18 	924.719
    21 	153   	622.135	91.1509	439.18 	898.276
    22 	132   	609.145	90.9044	414.759	881.22 
    23 	144   	606.942	99.9945	398.425	896.75 
    24 	154   	607.987	93.5085	398.425	900.884
    25 	154   	614.743	96.834 	414.759	853.219
    26 	148   	619.891	94.4711	414.759	904.185
    27 	159   	615.82 	85.6307	342.606	804.844
    28 	139   	611.906	90.8058	342.606	865.811
    29 	131   	605.906	92.8274	376.479	858.809
    30 	133   	610.802	89.235 	376.479	854.539
    31 	150   	620.746	92.4849	347.747	898.484
    32 	150   	633.816	96.8833	347.747	848.105
    33 	122   	605.245	82.5861	461.519	850.322
    34 	136   	605.907	87.4045	455.886	805.494
    35 	150   	613.93 	90.5069	439.717	833.191
    36 	143   	615.437	89.8362	448.975	891.014
    37 	155   	626.868	97.3996	448.975	863.669
    38 	143   	605.845	93.2684	400.593	880.837
    39 	156   	618.728	89.2249	417.003	846.104
    40 	158   	615.108	87.9471	412.018	892.327
    41 	147   	612.426	87.8064	412.018	850.3  
    42 	161   	617.258	89.74  	412.018	878.717
    43 	142   	598.385	82.9323	364.204	807.321
    44 	161   	618.88 	99.5308	364.204	863.889
    45 	144   	620.402	101.472	413.767	898.001
    46 	154   	619.989	94.6417	413.767	843.491
    47 	149   	620.219	94.0138	413.767	872.909
    48 	150   	623.76 	89.0978	435.689	857.686
    49 	142   	610.458	96.8607	416.293	879.229
    50 	134   	610.428	96.5349	416.293	965.44 
    51 	144   	610.099	90.7105	416.293	864.423
    52 	151   	606.891	92.1193	412.897	898.567
    53 	160   	615.897	89.2048	420.063	883.352
    54 	154   	611.504	86.4881	384.11 	851.355
    55 	160   	621.214	89.7605	390.348	922.545
    56 	137   	621.134	94.8716	386.73 	889.607
    57 	147   	611.827	92.4354	386.73 	886.414
    58 	151   	613.889	85.8398	386.73 	846.488
    59 	163   	618.961	92.3281	386.73 	912.147
    60 	147   	606.135	95.4461	386.73 	799.906
    61 	145   	599.177	100.464	386.73 	918.148
    62 	140   	596.29 	103.138	407.975	838.963
    63 	155   	598.97 	104.974	399.679	950.353
    64 	131   	590.668	111.906	399.679	887.453
    65 	151   	608.757	107.644	414.235	883.795
    66 	143   	586.678	99.8318	409.461	902.711
    67 	146   	597.168	103.958	409.461	918.553
    68 	153   	592.626	99.5577	401.98 	861.703
    69 	132   	586.817	102.877	401.98 	871.028
    70 	137   	576.783	100.241	374.134	810.682
    71 	144   	580.324	111.737	374.134	899.763
    72 	155   	587.824	96.4835	378.306	826.919
    73 	149   	591.233	103.414	378.306	848.464
    74 	146   	598.649	102.959	364.068	871.585
    75 	141   	593.202	106.871	378.306	815.996
    76 	141   	592.947	99.1806	378.306	816.309
    77 	144   	594.647	98.3097	401.786	892.711
    78 	153   	599.18 	103.961	401.786	882.52 
    79 	138   	583.153	105.373	342.556	841.103
    80 	155   	601.218	103.075	342.556	858.644
    81 	146   	589.758	109.763	317.582	875.008
    82 	141   	597.814	106.902	342.556	906.727
    83 	143   	595.112	98.2713	397.56 	828.849
    84 	144   	601.375	102.444	397.56 	893.868
    85 	137   	584.082	95.8824	369.167	868.654
    86 	142   	585.447	106.479	369.167	919.349
    87 	148   	584.884	100.315	380.191	829.273
    88 	146   	596.739	102.949	380.191	849.355
    89 	146   	603.621	97.2974	380.191	865.493
    90 	154   	610.267	97.4239	449.524	895.541
    91 	148   	604.385	92.8878	393.602	900.65 
    92 	146   	596.254	90.6152	377.784	821.835
    93 	145   	602.367	89.1771	377.784	894.626
    94 	147   	605.487	96.1223	377.784	891.553
    95 	156   	609.273	96.9593	377.784	839.919
    96 	159   	596.615	91.5023	349.644	806.063
    97 	146   	602.137	95.613 	349.644	905.014
    98 	160   	597.269	95.1558	390.21 	835.139
    99 	150   	581.713	88.372 	390.21 	780.696
    100	149   	590.036	98.4911	340.685	842.513
    101	145   	594.842	102.32 	340.685	812.099
    102	145   	591.583	101.987	340.685	819.834
    103	146   	586.822	116.159	340.685	961.222
    104	149   	598.939	105.974	340.685	866.798
    105	142   	592.032	95.8593	328.899	865.973
    106	140   	585.267	106.222	318.955	883.363
    107	148   	587.732	106.592	328.899	856.287
    108	163   	590.005	93.5052	390.21 	868.732
    109	150   	593.998	97.9191	399.661	850.379
    110	155   	587.238	93.3875	346.807	882.84 
    111	145   	592.179	100.63 	346.807	882.36 
    112	133   	579.662	96.732 	346.807	865.363
    113	133   	577.834	95.2702	344.75 	825.723
    114	145   	600.461	100.232	346.807	846.283
    115	146   	585.689	100.147	346.807	863.542
    116	159   	607.494	101.154	346.807	851.886
    117	160   	598.754	93.6461	346.807	897.75 
    118	144   	594.531	87.9266	346.807	799.927
    119	146   	600.983	89.7996	392.053	835.43 
    120	123   	590.145	99.6178	383.331	927.474
    121	151   	577.331	90.5086	392.053	848.591
    122	140   	583.552	102.932	392.053	859.359
    123	153   	603.32 	100.266	336.52 	867.913
    124	142   	592.551	98.2895	336.52 	877.013
    125	139   	602.544	105.631	336.52 	941.727
    126	141   	597.774	101.001	336.52 	903.286
    127	146   	589.245	94.018 	348.27 	839.544
    128	149   	601.697	95.4355	348.27 	870.068
    129	156   	594.255	88.1518	400.433	919.061
    130	153   	598.717	91.5016	360.762	839.044
    131	148   	609.811	102.587	360.762	894.364
    132	135   	596.405	93.0674	360.762	844.391
    133	138   	600.701	101.49 	360.762	850.958
    134	139   	597.136	104.378	360.762	880.864
    135	146   	614.275	104.635	360.762	884.376
    136	149   	596.863	94.9803	360.762	889.67 
    137	141   	593.37 	113.412	360.762	970.732
    138	151   	595.896	104.946	344.775	888.112
    139	156   	604.163	99.5229	344.775	819.933
    140	138   	595.839	96.3621	360.762	856.111
    141	155   	605.624	103.671	360.762	962.1  
    142	162   	603.625	94.0956	360.762	873.828
    143	139   	595.102	82.5992	391.656	921.484
    144	144   	598.406	95.7784	381.215	861.924
    145	134   	594.89 	92.0286	355.365	848.736
    146	147   	590.889	87.9088	355.365	807.406
    147	140   	589.291	97.7183	381.215	880.184
    148	143   	604.856	99.1614	391.656	853.367
    149	140   	598.659	100.526	382.99 	883.613
    150	141   	588.401	92.9983	382.99 	816.608
    151	150   	601.411	106.17 	376.954	872.771
    152	139   	605.276	95.7904	391.656	847.436
    153	147   	599.941	98.6259	370.696	845.273
    154	165   	605.472	90.6497	391.656	852.442
    155	151   	605.455	92.8414	414.418	874.544
    156	162   	600.926	85.6537	414.418	843.022
    157	141   	592.059	89.3239	406.141	817.025
    158	141   	602.702	89.1685	414.418	891.501
    159	155   	621.426	91.4592	414.418	850.561
    160	137   	597.681	88.2213	414.418	828.274
    161	152   	617.349	100.492	405.856	852.43 
    162	144   	607.967	100.219	415.749	863.014
    163	144   	597.438	94.4677	374.057	853.395
    164	143   	606.649	106.269	417.212	927.626
    165	139   	601.061	96.1181	417.212	876.191
    166	138   	608.182	94.6305	417.212	874.352
    167	142   	606.341	102.96 	417.212	857.715
    168	154   	612.315	100.458	417.212	853.163
    169	144   	600.548	94.6036	389.043	912.677
    170	147   	596.326	93.1186	387.175	857.377
    171	151   	596.977	96.7877	417.355	916.968
    172	154   	601.28 	96.2508	413.302	861.239
    173	156   	595.5  	89.7786	358.787	846.475
    174	153   	598.559	90.441 	388.117	841.884
    175	159   	599.361	76.5572	388.117	809.678
    176	146   	605.174	80.0781	388.117	845.562
    177	152   	603.332	87.9707	402.822	865.972
    178	149   	601.575	85.8932	402.822	819.41 
    179	147   	596.651	85.7033	408.2  	811.55 
    180	148   	602.271	92.7995	409.478	873.351
    181	149   	605.633	91.6442	415.586	849.937
    182	153   	617.046	86.7802	437.072	846.955
    183	141   	617.407	93.4319	392.197	938.941
    184	140   	612.417	93.3851	442.852	914.159
    185	136   	596.893	91.5885	408.708	860.199
    186	149   	601.23 	93.8262	397.826	870.708
    187	138   	597.682	89.6111	447.327	865.306
    188	154   	608.569	93.5705	427.847	889.18 
    189	130   	595.448	93.9506	355.013	812.869
    190	143   	604.446	88.7994	450.377	847.469
    191	154   	603.6  	92.1093	360.186	849.777
    192	142   	601.09 	95.1065	360.186	929.13 
    193	157   	611.321	84.6007	402.369	840.993
    194	148   	614.902	91.5541	402.369	871.742
    195	146   	598.961	88.846 	414.413	828.086
    196	147   	585.712	99.989 	414.413	938.569
    197	138   	596.541	104.046	401.733	881.945
    198	148   	589.805	87.2444	401.733	838.474
    199	136   	589.293	94.0039	401.733	865.789
    200	144   	581.681	95.4379	382.09 	844.959
    [Finished in 19.1s]