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Test Data (111119_20)
magnific0 edited this page Feb 25, 2014
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1 revision
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: 118.43846189
Mean: 643.432600402
Std: 250.087001416
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 0.000146901344124
Mean: 1.78100847175
Std: 14.3962711691
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:2 restart:1 ftol:1e-30 xtol:1e-30
Best: 0.000127275661725
Mean: 34.6438548664
Std: 84.2933447339
Algorithm name: Simulated Annealing (Corana's) - iter:10000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 0.0101744354279
Mean: 327.547133924
Std: 182.890824657
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: 0.00013866289828
Mean: 0.000217185862625
Std: 3.48588443305e-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: 3.34456018267
Mean: 503.182782222
Std: 179.887339228
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: 532.983510263
Mean: 1603.1677137
Std: 392.231643559
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 3.97494071572
Mean: 386.712888328
Std: 141.614772194
Testing problem: Michalewicz, 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: -9.62254014588
Mean: -8.90130900097
Std: 0.44734162405
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: -9.65973136361
Mean: -9.50208731406
Std: 0.12845441311
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:2 restart:1 ftol:1e-30 xtol:1e-30
Best: -9.66015171564
Mean: -9.5698853692
Std: 0.12635202931
Algorithm name: Simulated Annealing (Corana's) - iter:10000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: -9.57498328364
Mean: -9.01120318273
Std: 0.295751563558
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: -9.66014959618
Mean: -9.61761640842
Std: 0.0395712419707
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: -9.62351580655
Mean: -9.33774991226
Std: 0.255297543278
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: -9.57236483907
Mean: -8.15568412567
Std: 1.0777489425
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: -9.57832781025
Mean: -9.21615914475
Std: 0.179424566528
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: 0.0108385871567
Mean: 6.76975512188
Std: 3.24050207334
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 1.13161998921
Mean: 5.89030623413
Std: 2.15483617788
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:2 restart:1 ftol:1e-30 xtol:1e-30
Best: 0.0
Mean: 1.40304973105
Std: 2.21843537124
Algorithm name: Simulated Annealing (Corana's) - iter:10000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 1.01016875476
Mean: 5.28125116523
Std: 2.200336447
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: 4.64194000926e-06
Mean: 0.28945063029
Std: 0.418845681611
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: 0.105260363487
Mean: 0.836429917998
Std: 0.499357596299
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: 2.98487717128
Mean: 26.8549353237
Std: 15.8977134547
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 0.15203453213
Mean: 3.3715604705
Std: 1.4613502891
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: 0.0104280967906
Mean: 4.82984549323
Std: 1.7006258767
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 0.21621815424
Mean: 1.70095674027
Std: 0.859241781638
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:2 restart:1 ftol:1e-30 xtol:1e-30
Best: 0.00255681019163
Mean: 7.07146658777
Std: 14.3802360962
Algorithm name: Simulated Annealing (Corana's) - iter:10000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 0.0300038373841
Mean: 6.31653132495
Std: 17.833736972
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: 4.35121373216
Mean: 20.8714713051
Std: 23.5095405517
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: 1.47037835994
Mean: 50.7543339276
Std: 105.856754654
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: 5.17689969051e-30
Mean: 0.38092847304
Std: 1.16856599668
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 0.424583809807
Mean: 6.12984536854
Std: 4.20040744656
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: 5.06328068361e-08
Mean: 5.56060148789e-07
Std: 4.78701566141e-07
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 4.81971553836e-05
Mean: 0.000220345490541
Std: 0.0001384347688
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:2 restart:1 ftol:1e-30 xtol:1e-30
Best: 2.68720601326e-10
Mean: 0.796274633345
Std: 1.20375493894
Algorithm name: Simulated Annealing (Corana's) - iter:10000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 0.0372698026599
Mean: 0.0866506861488
Std: 0.0264482770829
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: 0.000890847043575
Mean: 0.00150905650446
Std: 0.000263119977884
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: 0.207865727772
Mean: 0.560867014059
Std: 0.224541207938
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: 10.8709531911
Std: 8.02173885988
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 0.000119595757156
Mean: 0.0914664181722
Std: 0.215594695841
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: 7.55361745375e-08
Mean: 0.0563331820811
Std: 0.0333595711659
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 0.0914494179089
Mean: 0.234522467463
Std: 0.0613157593169
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:2 restart:1 ftol:1e-30 xtol:1e-30
Best: 2.10942374679e-15
Mean: 0.195540753798
Std: 0.512255324833
Algorithm name: Simulated Annealing (Corana's) - iter:10000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 0.0990216028569
Mean: 0.327355187712
Std: 0.142434452069
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: 4.48434471541e-05
Mean: 0.026351420954
Std: 0.0184568318753
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: 0.220138447922
Mean: 0.740917755764
Std: 0.243757993137
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: 0.142348922271
Std: 0.25470860873
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 1.13406315779e-05
Mean: 0.0938915796562
Std: 0.0613281955833
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: 5.36624718696
Mean: 12.4736392514
Std: 3.43760315923
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 4.93815511835
Mean: 9.26849656136
Std: 3.47466032627
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:2 restart:1 ftol:1e-30 xtol:1e-30
Best: 4.93130017864
Mean: 11.101947086
Std: 3.94369681757
Algorithm name: Simulated Annealing (Corana's) - iter:10000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 5.43375730529
Mean: 20.7269376453
Std: 13.3674146153
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: 5.34990531295
Mean: 12.9967523793
Std: 2.90361027197
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: 5.71388460871
Mean: 29.0194350984
Std: 18.3589803902
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: 5.30342237193
Mean: 21.9877577459
Std: 13.4211428295
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 5.88819264893
Mean: 13.1639242265
Std: 3.29753389512
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: 13.3764775913
Mean: 23.1114720478
Std: 3.71896505119
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 22.784566535
Mean: 29.7451428486
Std: 2.59601666732
Algorithm name: DE - Self adaptive - gen:500 variant:2 self_adaptation:2 restart:1 ftol:1e-30 xtol:1e-30
Best: 15.3636348583
Mean: 26.0885334432
Std: 3.42659332202
Algorithm name: Simulated Annealing (Corana's) - iter:10000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 13.0165727312
Mean: 25.8725396007
Std: 7.58609216686
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: 12.953447471
Mean: 21.5267300589
Std: 4.51230340479
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: 17.4014632111
Mean: 32.7722830459
Std: 7.31533417565
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: 21.232931071
Mean: 38.5310154037
Std: 10.9050169002
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 15.8269688453
Mean: 30.0738891474
Std: 4.3745121463