This repository has been archived by the owner on Jul 16, 2024.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 (1112_20)
magnific0 edited this page Feb 25, 2014
·
1 revision
Trials: 200 - Population size: 20 - Generations: 500
Testing problem: Schwefel, Dimension: 10
With Population Size: 20
Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4
Best: 4.30645823144e-05
Mean: 651.394879358
Std: 251.229338288
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 1.07483892862e-05
Mean: 0.00388187915198
Std: 0.00959401802026
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: 0.0
Mean: 5.92191673072
Std: 25.8130365813
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: 1.18439022804
Std: 11.78446481
Algorithm name: Simulated Annealing (Corana's) - iter:10000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 0.0400135789769
Mean: 286.194604306
Std: 157.851760567
Algorithm name: Improved Harmony Search - iter:10000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: 2.90116286124e-05
Mean: 7.4742982838e-05
Std: 2.49823302685e-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: 1.07148979237
Mean: 513.51354284
Std: 175.429130076
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1 homebrew variant?:0
Best: 1263.34768108
Mean: 1977.95947972
Std: 248.606803221
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 127.509800201
Mean: 393.355049378
Std: 123.3755637
Testing problem: Rastrigin, Dimension: 10
With Population Size: 20
Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4
Best: 0.0078899633714
Mean: 6.76042270023
Std: 3.29429896928
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 0.0145417868053
Mean: 5.64314807019
Std: 2.17984291709
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: 0.0
Mean: 0.0298487717129
Std: 0.16972730065
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: 1.36424205266e-14
Std: 1.77759786616e-13
Algorithm name: Simulated Annealing (Corana's) - iter:10000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 1.03208597797
Mean: 4.4625225346
Std: 2.11145776955
Algorithm name: Improved Harmony Search - iter:10000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: 5.69444588905e-06
Mean: 0.364106089145
Std: 0.455546304099
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: 0.120172678467
Mean: 0.81006131302
Std: 0.535162662656
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1 homebrew variant?:0
Best: 1.98991811419
Mean: 7.32786947448
Std: 3.51795591016
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 0.194794065931
Mean: 3.20115543481
Std: 1.39035428209
Testing problem: Rosenbrock, Dimension: 10
With Population Size: 20
Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4
Best: 0.00467872588281
Mean: 6.17636580497
Std: 10.9740429782
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 0.312004624536
Mean: 1.71617759443
Std: 0.799315640188
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: 0.000165006153006
Mean: 2.88528749096
Std: 2.09842797134
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: 3.65140159048
Mean: 5.77102794012
Std: 0.416334188895
Algorithm name: Simulated Annealing (Corana's) - iter:10000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 0.0174085023484
Mean: 4.16789390894
Std: 12.6016301806
Algorithm name: Improved Harmony Search - iter:10000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: 0.193199135949
Mean: 17.4203183761
Std: 21.8961344362
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: 1.05871941343
Mean: 77.8713252522
Std: 151.523113481
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1 homebrew variant?:0
Best: 6.822414235e-29
Mean: 0.0598007849464
Std: 0.484578230832
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 0.462179493801
Mean: 6.89147436206
Std: 4.96891467548
Testing problem: Ackley, Dimension: 10
With Population Size: 20
Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4
Best: 4.40516392253e-08
Mean: 0.0057761537288
Std: 0.0814768455758
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 5.6524616618e-05
Mean: 0.000221436965868
Std: 0.000130619212531
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: 1.58444368736e-10
Mean: 1.20559873196e-09
Std: 9.61389806144e-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: 1.51326062792e-12
Std: 4.02826987083e-12
Algorithm name: Simulated Annealing (Corana's) - iter:10000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 0.0299271302485
Mean: 0.0958560552527
Std: 0.0299021550571
Algorithm name: Improved Harmony Search - iter:10000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: 0.000785618315945
Mean: 0.00139018280702
Std: 0.000250356435306
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: 0.16723237379
Mean: 0.547689423043
Std: 0.186639650037
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1 homebrew variant?:0
Best: 3.99680288865e-15
Mean: 4.77839989799e-15
Std: 1.47169850899e-15
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 0.000104171424802
Mean: 0.114778109573
Std: 0.235290613421
Testing problem: Griewank, Dimension: 10
With Population Size: 20
Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4
Best: 5.32421478017e-07
Mean: 0.0556710714828
Std: 0.0301049234739
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 0.0196614001529
Mean: 0.222144243274
Std: 0.0669502220711
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: 3.96349619791e-14
Mean: 0.00496187752766
Std: 0.00599593287376
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: 2.38135674265e-06
Std: 2.05456189368e-05
Algorithm name: Simulated Annealing (Corana's) - iter:10000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 0.103177544776
Mean: 0.322542596631
Std: 0.122255753156
Algorithm name: Improved Harmony Search - iter:10000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: 8.42245221307e-05
Mean: 0.0250932313674
Std: 0.0180802625311
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: 0.193855763523
Mean: 0.770338094621
Std: 0.232949388527
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1 homebrew variant?:0
Best: 0.0
Mean: 0.00392946704771
Std: 0.00580161862706
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 0.00217580093109
Mean: 0.0934743479292
Std: 0.05754536118
Testing problem: Levy5, Dimension: 10
With Population Size: 20
Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4
Best: -4358.28132462
Mean: -3564.81227177
Std: 469.443751307
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: -3545.35242808
Mean: -2616.07564197
Std: 333.158633124
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: -4411.52297481
Mean: -4345.57240929
Std: 71.0798314648
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: -4411.52153501
Mean: -4249.35905824
Std: 141.888174431
Algorithm name: Simulated Annealing (Corana's) - iter:10000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: -4307.26345439
Mean: -3575.93562518
Std: 419.380633814
Algorithm name: Improved Harmony Search - iter:10000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: -4411.4238652
Mean: -4118.79395277
Std: 303.619970435
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: -4198.6636025
Mean: -3434.3223874
Std: 398.211591029
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1 homebrew variant?:0
Best: -3783.7547904
Mean: -2322.79848319
Std: 613.278134571
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: -3926.49059874
Mean: -2960.53364488
Std: 374.944954747
Testing problem: Cassini 1, Dimension: 6
With Population Size: 20
Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4
Best: 5.34902024962
Mean: 12.0470260923
Std: 3.72526256845
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 4.93175049115
Mean: 9.19987270017
Std: 3.43164676361
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: 4.94745867533
Mean: 9.49392821951
Std: 3.46098949355
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: 5.53873610925
Mean: 10.8808537423
Std: 3.68863789746
Algorithm name: Simulated Annealing (Corana's) - iter:10000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 5.22879972636
Mean: 21.8180939278
Std: 14.376269847
Algorithm name: Improved Harmony Search - iter:10000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: 5.0678077259
Mean: 12.6277626644
Std: 3.48563167213
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: 7.30246647346
Mean: 29.0549508714
Std: 17.6659890011
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1 homebrew variant?:0
Best: 10.9964850603
Mean: 15.8824718863
Std: 2.04571161966
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 6.23750922563
Mean: 12.9044103642
Std: 3.15029492662
Testing problem: GTOC_1, Dimension: 8
With Population Size: 20
Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4
Best: -1142482.41289
Mean: -429906.43868
Std: 274005.693038
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: -840036.731242
Mean: -253702.737031
Std: 141255.915601
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: -966198.787989
Mean: -375224.600221
Std: 171826.705833
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: -963918.637061
Mean: -439062.750173
Std: 170618.334618
Algorithm name: Simulated Annealing (Corana's) - iter:10000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: -811660.798749
Mean: -84484.3514644
Std: 156125.646228
Algorithm name: Improved Harmony Search - iter:10000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: -1373683.73279
Mean: -720228.011413
Std: 208409.500393
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: -736924.897307
Mean: -67194.4474029
Std: 127638.91447
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1 homebrew variant?:0
Best: -938419.052966
Mean: -86634.6938907
Std: 131239.33798
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: -740791.705221
Mean: -177839.103037
Std: 158451.50548
Testing problem: Cassini 2, Dimension: 22
With Population Size: 20
Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4
Best: 13.7985878688
Mean: 23.0227452165
Std: 3.90216199707
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 22.894839677
Mean: 29.4646371123
Std: 2.43393315804
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: 17.5003903972
Mean: 25.8587028553
Std: 2.97435928101
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: 14.0215919686
Mean: 24.0335648591
Std: 3.28928740432
Algorithm name: Simulated Annealing (Corana's) - iter:10000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 10.8721384102
Mean: 27.0971000907
Std: 7.81377431952
Algorithm name: Improved Harmony Search - iter:10000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: 12.5495066295
Mean: 21.1247159748
Std: 4.10045482823
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: 20.1467636184
Mean: 32.4603483254
Std: 6.42532184499
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1 homebrew variant?:0
Best: 16.7364303453
Mean: 23.6886964582
Std: 3.2220250149
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 16.3754846987
Mean: 29.21204124
Std: 4.32331245129
Testing problem: Messenger full, Dimension: 26
With Population Size: 20
Algorithm name: Particle Swarm optimization - gen:500 omega:0.7298 eta1:2.05 eta2:2.05 variant:5 topology:2 topology param.:4
Best: 11.4175928823
Mean: 20.2300157148
Std: 3.52828750895
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 19.5129943483
Mean: 30.126446111
Std: 3.5797501741
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:1 restart:1 ftol:1e-30 xtol:1e-30
Best: 14.8621005753
Mean: 26.3702179085
Std: 3.56582599536
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: 13.0658484438
Mean: 24.4738401046
Std: 3.89461755575
Algorithm name: Simulated Annealing (Corana's) - iter:10000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 8.47734739916
Mean: 24.2822647292
Std: 8.61439509615
Algorithm name: Improved Harmony Search - iter:10000 phmcr:0.85 ppar_min:0.35 ppar_max:0.99 bw_min:1e-05 bw_max:1
Best: 12.2416552291
Mean: 22.5525507985
Std: 4.6270987426
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: 12.8121933522
Mean: 32.2455070871
Std: 9.62971558435
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 restart:1 homebrew variant?:0
Best: 14.2821501254
Mean: 18.2570063976
Std: 2.50739588242
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
matplotlib Best: 15.4751256634
Mean: 32.2349080666
Std: 5.68150377029