This repository has been archived by the owner on Jul 16, 2024. It is now read-only.
-
Notifications
You must be signed in to change notification settings - Fork 86
Test Data (1111_50)
magnific0 edited this page Feb 25, 2014
·
1 revision
Trials: 200 - Population size: 50 - Generations: 500
Testing problem: Schwefel, Dimension: 10
With Population Size: 50
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: 455.496318355
Std: 192.110633283
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 0.000242926885221
Mean: 0.00538739578439
Std: 0.00919600260789
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: 0.0
Mean: 4.13820089307e-13
Std: 4.52901879437e-13
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: 6.36646291241e-12
Mean: 7.06604168954e-09
Std: 2.42628864483e-08
Algorithm name: Simulated Annealing (Corana's) - iter:25000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 0.030176124963
Mean: 263.979867076
Std: 151.905446654
Algorithm name: Improved Harmony Search - iter:25000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: 2.13009416257e-05
Mean: 5.58535759455e-05
Std: 1.8474876993e-05
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: 3.64538224619
Mean: 436.028532316
Std: 177.010036241
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: 592.22457455
Mean: 1528.34594684
Std: 384.410542144
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 0.0136808324778
Mean: 115.800225027
Std: 79.3783537956
Testing problem: Rastrigin, Dimension: 10
With Population Size: 50
Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4
Best: 6.19460593043e-07
Mean: 4.32037495892
Std: 1.80658532164
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 1.72485586023
Mean: 5.30793620534
Std: 1.45288540287
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: 0.0
Mean: 3.29691829393e-14
Std: 5.2054420955e-14
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:25000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 1.00618874368
Mean: 5.3521559072
Std: 2.42120105593
Algorithm name: Improved Harmony Search - iter:25000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: 3.52724025277e-06
Mean: 0.000170653384358
Std: 0.0016282186511
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: 0.0954000135637
Mean: 0.457604929672
Std: 0.291375746985
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: 1.98991811419
Mean: 13.1831848494
Std: 10.0504092982
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 0.00017935969629
Mean: 0.184824272666
Std: 0.318767994286
Testing problem: Rosenbrock, Dimension: 10
With Population Size: 50
Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4
Best: 0.000337117219914
Mean: 3.60086645068
Std: 1.69448398871
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 0.225493318228
Mean: 1.17261214808
Std: 0.497558853284
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: 5.9143858449e-05
Mean: 2.37194588595
Std: 1.54160220713
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: 4.46014585872
Mean: 5.18218947351
Std: 0.298549390665
Algorithm name: Simulated Annealing (Corana's) - iter:25000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 0.0190307327619
Mean: 2.17824559498
Std: 7.53152064792
Algorithm name: Improved Harmony Search - iter:25000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: 5.45744865317
Mean: 10.5867118795
Std: 12.639175155
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: 2.01042940753
Mean: 37.8848883142
Std: 67.8013268314
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: 0.0797315822469
Std: 0.558121075729
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 0.123202895205
Mean: 1.36003762292
Std: 0.721448323844
Testing problem: Ackley, Dimension: 10
With Population Size: 50
Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4
Best: 2.09503991933e-08
Mean: 1.92741810956e-07
Std: 1.35818764363e-07
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 0.00016188270346
Mean: 0.000397528223809
Std: 0.000123870934272
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: 1.93058458109e-10
Mean: 9.17691114211e-10
Std: 4.9280253851e-10
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: 1.39657174714e-13
Std: 7.21001781624e-13
Algorithm name: Simulated Annealing (Corana's) - iter:25000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 0.0197723301744
Mean: 0.0854553740541
Std: 0.0284610841302
Algorithm name: Improved Harmony Search - iter:25000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: 0.000630907974767
Mean: 0.00119050374069
Std: 0.000181133613314
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: 0.0733676932552
Mean: 0.369832193809
Std: 0.152089227014
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: 6.37706568556
Std: 8.06976558409
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 0.000111331320899
Mean: 0.00187323923764
Std: 0.00166703960006
Testing problem: Griewank, Dimension: 10
With Population Size: 50
Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4
Best: 7.82152120848e-13
Mean: 0.0314420829534
Std: 0.0168662932499
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 0.0947072376727
Mean: 0.221419367671
Std: 0.0488948010115
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: 5.49414846951e-10
Mean: 0.000890321227839
Std: 0.00197673620743
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: 5.92318416537e-13
Std: 4.17317981015e-12
Algorithm name: Simulated Annealing (Corana's) - iter:25000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 0.10618232233
Mean: 0.328816209292
Std: 0.12625851326
Algorithm name: Improved Harmony Search - iter:25000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: 4.10977910502e-05
Mean: 0.00843060815094
Std: 0.00769458792411
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: 0.236610948519
Mean: 0.739486828045
Std: 0.235266786396
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: 0.0151791885057
Std: 0.0151566564222
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 2.89261438446e-05
Mean: 0.0150109548529
Std: 0.0112010091507
Testing problem: Levy5, Dimension: 10
With Population Size: 50
Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4
Best: -4363.86143571
Mean: -3798.2075356
Std: 376.832011082
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: -3528.5344002
Mean: -2729.40943366
Std: 270.062205847
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: -4411.48553023
Mean: -4373.95017915
Std: 34.8560353779
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: -4411.52232291
Mean: -4363.87248507
Std: 56.3460764887
Algorithm name: Simulated Annealing (Corana's) - iter:25000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: -4341.87127633
Mean: -3531.58104493
Std: 420.580258745
Algorithm name: Improved Harmony Search - iter:25000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: -4411.45024042
Mean: -4335.99132214
Std: 137.332219846
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: -4233.63671073
Mean: -3653.33187315
Std: 377.746871006
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: -4291.61681505
Mean: -21.5805934967
Std: 4685.70169683
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: -4291.21869424
Mean: -3940.28675411
Std: 185.677111078
Testing problem: Cassini 1, Dimension: 6
With Population Size: 50
Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4
Best: 5.00272083736
Mean: 10.4037241239
Std: 2.97936900463
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 5.30346126676
Mean: 6.43008224605
Std: 2.29263524947
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: 5.3036003117
Mean: 6.79580852804
Std: 2.19295923515
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: 5.50795046523
Mean: 7.71123966011
Std: 2.05675618708
Algorithm name: Simulated Annealing (Corana's) - iter:25000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 5.36671534157
Mean: 17.5798284356
Std: 10.3221443445
Algorithm name: Improved Harmony Search - iter:25000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: 5.33885977842
Mean: 11.6709938806
Std: 3.60596068686
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: 5.60821087927
Mean: 17.9163604298
Std: 7.00176084998
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: 5.30342237191
Mean: 20.5692047842
Std: 15.7343336524
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 5.77747750534
Mean: 10.9351807538
Std: 2.25146315094
Testing problem: GTOC_1, Dimension: 8
With Population Size: 50
Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4
Best: -1245129.09159
Mean: -634535.449315
Std: 219284.905012
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: -746840.181024
Mean: -341566.427298
Std: 132575.207866
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: -957385.832824
Mean: -513362.295871
Std: 144289.140219
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: -955930.592771
Mean: -552219.386721
Std: 140359.344288
Algorithm name: Simulated Annealing (Corana's) - iter:25000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: -914299.02714
Mean: -117308.255185
Std: 198496.860094
Algorithm name: Improved Harmony Search - iter:25000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: -1218485.26147
Mean: -825286.610248
Std: 158358.107181
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: -757406.00736
Mean: -135677.293183
Std: 181813.445906
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: -1241618.61143
Mean: -168959.495057
Std: 262095.732893
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: -883225.489476
Mean: -371888.42208
Std: 186306.134401
Testing problem: Cassini 2, Dimension: 22
With Population Size: 50
Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4
Best: 12.3059123724
Mean: 20.3776188557
Std: 2.92037095234
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 21.06757745
Mean: 27.6546417183
Std: 2.22291180918
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: 17.1153837891
Mean: 23.4857363949
Std: 2.54670028042
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: 12.6743383908
Mean: 21.9032919418
Std: 3.16202705815
Algorithm name: Simulated Annealing (Corana's) - iter:25000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 10.5340776426
Mean: 23.6029625934
Std: 5.74337858643
Algorithm name: Improved Harmony Search - iter:25000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: 12.2697523988
Mean: 19.3063218005
Std: 3.99020046545
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: 15.6607301492
Mean: 27.713921582
Std: 4.95659090126
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: 14.4224569806
Mean: 27.9902114264
Std: 7.56586710613
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 13.8390113469
Mean: 25.7586778878
Std: 3.24868317112
Testing problem: Messenger full, Dimension: 26
With Population Size: 50
Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4
Best: 10.7985211087
Mean: 17.8870880042
Std: 2.546731442
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 17.0476938298
Mean: 28.1578496907
Std: 3.34050164096
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: 17.6210790338
Mean: 24.0196678539
Std: 2.81594320317
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: 13.797169166
Mean: 22.0407378205
Std: 3.06714848715
Algorithm name: Simulated Annealing (Corana's) - iter:25000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 8.96311376576
Mean: 21.9264446189
Std: 7.62402765453
Algorithm name: Improved Harmony Search - iter:25000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: 16.4929571966
Mean: 21.4225224398
Std: 2.86294930037
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: 13.0756949382
Mean: 24.6380674523
Std: 5.64310813543
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: 11.657322204
Mean: 25.8141356738
Std: 9.64012732446
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 13.5434076338
Mean: 25.726801883
Std: 4.14409297815