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Test Data (1111_10)

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magnific0 edited this page Feb 25, 2014 · 1 revision 
Trials: 200 - Population size: 10 - Generations: 500
Testing problem: Schwefel, Dimension: 10
With Population Size: 10
    Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4 
    Best:  118.438334614
    Mean:  854.137776905
    Std:   313.348258848
    Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
    Best:  1.98342604563e-08
    Mean:  65.8334027128
    Std:   96.5889761998
    Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
    Best:  0.0
    Mean:  102.757545652
    Std:   116.020477025
    Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] restart:1 ftol:1e-30 xtol:1e-30
    Best:  5.45696821064e-12
    Mean:  46.3352090924
    Std:   78.0288502538
    Algorithm name: Simulated Annealing (Corana's) - iter:5000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1 
    Best:  0.0237654348903
    Mean:  293.201821343
    Std:   184.400177231
    Algorithm name: Improved Harmony Search - iter:5000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1 
    Best:  2.84811039819e-05
    Mean:  0.343312664039
    Std:   1.68897126018
    Algorithm name: A Simple Genetic Algorithm - gen:500 CR:0.95 M:0.02 elitism:1 mutation:GAUSSIAN (0.1) selection:ROULETTE crossover:EXPONENTIAL 
    Best:  138.738501313
    Mean:  601.636577005
    Std:   180.794213634
    Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1
    Best:  473.753338458
    Mean:  1684.33953167
    Std:   412.199448869
    Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20 
    Best:  31.1439381169
    Mean:  549.21509892
    Std:   207.94868926
Testing problem: Rastrigin, Dimension: 10
With Population Size: 10
    Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4 
    Best:  0.000600999111214
    Mean:  9.62646130567
    Std:   5.05569004373
    Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
    Best:  0.00598974795129
    Mean:  4.56740575764
    Std:   2.65970424761
    Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
    Best:  0.0
    Mean:  0.804662842162
    Std:   1.12461640895
    Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] restart:1 ftol:1e-30 xtol:1e-30
    Best:  0.0
    Mean:  0.0
    Std:   0.0
    Algorithm name: Simulated Annealing (Corana's) - iter:5000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1 
    Best:  0.0401070146202
    Mean:  3.84856071002
    Std:   1.84693888153
    Algorithm name: Improved Harmony Search - iter:5000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1 
    Best:  2.99847687728e-05
    Mean:  2.13695915337
    Std:   1.11688888996
    Algorithm name: A Simple Genetic Algorithm - gen:500 CR:0.95 M:0.02 elitism:1 mutation:GAUSSIAN (0.1) selection:ROULETTE crossover:EXPONENTIAL 
    Best:  0.145647574726
    Mean:  2.50985739982
    Std:   1.22366710057
    Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1
    Best:  5.96975434256
    Mean:  39.8833635489
    Std:   18.8677328493
    Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20 
    Best:  0.0867182948051
    Mean:  5.68688796253
    Std:   3.0063138492
Testing problem: Rosenbrock, Dimension: 10
With Population Size: 10
    Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4 
    Best:  0.00130552853547
    Mean:  10.7230978429
    Std:   21.5670547891
    Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
    Best:  2.74288249641e-05
    Mean:  4.31169380885
    Std:   1.90876592579
    Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
    Best:  0.000352878352945
    Mean:  9.33147997268
    Std:   26.6711113345
    Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] restart:1 ftol:1e-30 xtol:1e-30
    Best:  4.16272052714
    Mean:  6.50565081684
    Std:   0.667022358834
    Algorithm name: Simulated Annealing (Corana's) - iter:5000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1 
    Best:  0.0218962619105
    Mean:  8.28365767746
    Std:   24.2114366615
    Algorithm name: Improved Harmony Search - iter:5000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1 
    Best:  5.3228677093
    Mean:  51.5540169378
    Std:   37.0919860088
    Algorithm name: A Simple Genetic Algorithm - gen:500 CR:0.95 M:0.02 elitism:1 mutation:GAUSSIAN (0.1) selection:ROULETTE crossover:EXPONENTIAL 
    Best:  2.88492423321
    Mean:  93.3875237534
    Std:   159.17102378
    Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1
    Best:  1.21434708604e-24
    Mean:  1.56664373472
    Std:   4.86077945366
    Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20 
    Best:  1.24555243323
    Mean:  11.6511982148
    Std:   11.3811888778
Testing problem: Ackley, Dimension: 10
With Population Size: 10
    Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4 
    Best:  6.66674293548e-08
    Mean:  0.35187213154
    Std:   1.38569093447
    Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
    Best:  2.18156396459e-06
    Mean:  0.0404576388398
    Std:   0.212287690095
    Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
    Best:  1.91481053236e-10
    Mean:  0.481279008947
    Std:   0.99768612915
    Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] restart:1 ftol:1e-30 xtol:1e-30
    Best:  4.4408920985e-16
    Mean:  1.49604773014e-13
    Std:   1.49673177181e-12
    Algorithm name: Simulated Annealing (Corana's) - iter:5000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1 
    Best:  0.0393058639155
    Mean:  0.0964959276057
    Std:   0.0321756631578
    Algorithm name: Improved Harmony Search - iter:5000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1 
    Best:  0.000821966455245
    Mean:  0.0812678040652
    Std:   0.259225865818
    Algorithm name: A Simple Genetic Algorithm - gen:500 CR:0.95 M:0.02 elitism:1 mutation:GAUSSIAN (0.1) selection:ROULETTE crossover:EXPONENTIAL 
    Best:  0.327086359807
    Mean:  1.22227413784
    Std:   0.441294155946
    Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1
    Best:  3.99680288865e-15
    Mean:  14.0001975958
    Std:   6.52414431161
    Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20 
    Best:  7.59035623088e-05
    Mean:  0.53944376616
    Std:   0.820932847991
Testing problem: Griewank, Dimension: 10
With Population Size: 10
    Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4 
    Best:  0.00739636316788
    Mean:  0.0836707859666
    Std:   0.0538302787613
    Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
    Best:  1.72993402936e-08
    Mean:  0.177610665484
    Std:   0.0899828634778
    Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
    Best:  6.10622663544e-15
    Mean:  0.0223165206926
    Std:   0.0308569206615
    Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] restart:1 ftol:1e-30 xtol:1e-30
    Best:  0.0
    Mean:  1.64613172596e-07
    Std:   2.32214958151e-06
    Algorithm name: Simulated Annealing (Corana's) - iter:5000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1 
    Best:  0.079250973305
    Mean:  0.294508793376
    Std:   0.110398808833
    Algorithm name: Improved Harmony Search - iter:5000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1 
    Best:  0.00024862147035
    Mean:  0.0690280785899
    Std:   0.0512683956689
    Algorithm name: A Simple Genetic Algorithm - gen:500 CR:0.95 M:0.02 elitism:1 mutation:GAUSSIAN (0.1) selection:ROULETTE crossover:EXPONENTIAL 
    Best:  0.398522957437
    Mean:  0.951736666203
    Std:   0.159498589279
    Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1
    Best:  0.0
    Mean:  0.217811885109
    Std:   0.336048041995
    Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20 
    Best:  0.0087672585569
    Mean:  0.159141233287
    Std:   0.131598334334
Testing problem: Levy5, Dimension: 10
With Population Size: 10
    Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4 
    Best:  -4268.00958756
    Mean:  -3164.24947238
    Std:   590.467168253
    Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
    Best:  -4006.49591054
    Mean:  -2614.2804384
    Std:   518.380179075
    Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
    Best:  -4411.52297573
    Mean:  -4240.55773511
    Std:   174.197274231
    Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] restart:1 ftol:1e-30 xtol:1e-30
    Best:  -4411.52297473
    Mean:  -4137.5108038
    Std:   262.358265261
    Algorithm name: Simulated Annealing (Corana's) - iter:5000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1 
    Best:  -4341.86546109
    Mean:  -3611.66321084
    Std:   382.875456263
    Algorithm name: Improved Harmony Search - iter:5000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1 
    Best:  -4329.17881407
    Mean:  -3517.92728781
    Std:   461.955737594
    Algorithm name: A Simple Genetic Algorithm - gen:500 CR:0.95 M:0.02 elitism:1 mutation:GAUSSIAN (0.1) selection:ROULETTE crossover:EXPONENTIAL 
    Best:  -4067.05612159
    Mean:  -2802.04284993
    Std:   422.609265001
    Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1
    Best:  -2800.7849418
    Mean:  4729.73119773
    Std:   8352.21403881
    Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20 
    Best:  -3685.12325718
    Mean:  -2390.57330726
    Std:   500.749838822
Testing problem: Cassini 1, Dimension: 6
With Population Size: 10
    Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4 
    Best:  5.34290293676
    Mean:  15.6970491474
    Std:   6.471599843
    Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
    Best:  4.93212616621
    Mean:  11.6328371121
    Std:   4.02320359275
    Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
    Best:  4.93800409561
    Mean:  12.125854792
    Std:   3.56077795967
    Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] restart:1 ftol:1e-30 xtol:1e-30
    Best:  5.46831240362
    Mean:  13.032479411
    Std:   4.01541166917
    Algorithm name: Simulated Annealing (Corana's) - iter:5000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1 
    Best:  5.21745805826
    Mean:  23.8450423328
    Std:   19.5422756077
    Algorithm name: Improved Harmony Search - iter:5000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1 
    Best:  5.27889711138
    Mean:  13.3024100356
    Std:   3.67038506145
    Algorithm name: A Simple Genetic Algorithm - gen:500 CR:0.95 M:0.02 elitism:1 mutation:GAUSSIAN (0.1) selection:ROULETTE crossover:EXPONENTIAL 
    Best:  6.41825471568
    Mean:  41.2512485653
    Std:   25.928815842
    Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1
    Best:  5.30581806631
    Mean:  33.8656207802
    Std:   26.9440413647
    Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20 
    Best:  5.68434013328
    Mean:  15.6217812963
    Std:   4.08403795217
Testing problem: GTOC_1, Dimension: 8
With Population Size: 10
    Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4 
    Best:  -1203640.88575
    Mean:  -323490.730643
    Std:   294422.392246
    Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
    Best:  -695409.106508
    Mean:  -214857.701358
    Std:   148633.529909
    Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
    Best:  -816539.318257
    Mean:  -256210.333925
    Std:   188031.897193
    Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] restart:1 ftol:1e-30 xtol:1e-30
    Best:  -868627.456746
    Mean:  -327010.259105
    Std:   164804.465739
    Algorithm name: Simulated Annealing (Corana's) - iter:5000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1 
    Best:  -724738.365376
    Mean:  -68952.7205104
    Std:   126996.55647
    Algorithm name: Improved Harmony Search - iter:5000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1 
    Best:  -1261324.40827
    Mean:  -558028.637134
    Std:   275217.88444
    Algorithm name: A Simple Genetic Algorithm - gen:500 CR:0.95 M:0.02 elitism:1 mutation:GAUSSIAN (0.1) selection:ROULETTE crossover:EXPONENTIAL 
    Best:  -626392.155254
    Mean:  -51704.1761825
    Std:   105528.956596
    Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1
    Best:  -593706.229879
    Mean:  -28982.7373382
    Std:   73059.7003888
    Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20 
    Best:  -582345.100418
    Mean:  -120912.579323
    Std:   127237.293155
Testing problem: Cassini 2, Dimension: 22
With Population Size: 10
    Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4 
    Best:  13.8047499183
    Mean:  25.9590747173
    Std:   4.49987538443
    Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
    Best:  22.7618647591
    Mean:  31.2392075435
    Std:   3.3715912811
    Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
    Best:  18.0169686035
    Mean:  28.1620914926
    Std:   3.39698818304
    Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] restart:1 ftol:1e-30 xtol:1e-30
    Best:  15.4891004502
    Mean:  26.8118032533
    Std:   4.17583945794
    Algorithm name: Simulated Annealing (Corana's) - iter:5000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1 
    Best:  13.4323007932
    Mean:  28.4835110692
    Std:   7.61066340488
    Algorithm name: Improved Harmony Search - iter:5000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1 
    Best:  13.151976394
    Mean:  23.9692181299
    Std:   4.3315041039
    Algorithm name: A Simple Genetic Algorithm - gen:500 CR:0.95 M:0.02 elitism:1 mutation:GAUSSIAN (0.1) selection:ROULETTE crossover:EXPONENTIAL 
    Best:  12.9929713168
    Mean:  38.0144975932
    Std:   10.0627948465
    Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1
    Best:  23.1008723014
    Mean:  46.1380511543
    Std:   13.451727537
    Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20 
    Best:  18.3382307716
    Mean:  33.0636739418
    Std:   5.30007117391
Testing problem: Messenger full, Dimension: 26
With Population Size: 10
    Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4 
    Best:  12.4347213498
    Mean:  22.8567358931
    Std:   5.04376296479
    Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
    Best:  19.8789392924
    Mean:  32.6579772488
    Std:   5.11030191744
    Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
    Best:  16.1426585564
    Mean:  28.9250695141
    Std:   4.56289230011
    Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] restart:1 ftol:1e-30 xtol:1e-30
    Best:  14.8211575128
    Mean:  28.3656007823
    Std:   4.85080601991
    Algorithm name: Simulated Annealing (Corana's) - iter:5000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1 
    Best:  11.4506971324
    Mean:  30.1739744234
    Std:   13.058113636
    Algorithm name: Improved Harmony Search - iter:5000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1 
    Best:  14.4376645676
    Mean:  25.2517455017
    Std:   6.1511564257
    Algorithm name: A Simple Genetic Algorithm - gen:500 CR:0.95 M:0.02 elitism:1 mutation:GAUSSIAN (0.1) selection:ROULETTE crossover:EXPONENTIAL 
    Best:  19.8971950949
    Mean:  42.2464754061
    Std:   13.5579888808
    Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1
    Best:  17.4049901699
    Mean:  50.5671119653
    Std:   15.6231787245
    Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20 
    Best:  20.6272501026
    Mean:  37.1778745376
 Std:   7.43833693599

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