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Test Data (1304_10)
magnific0 edited this page Feb 25, 2014
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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: 236.876669229
Mean: 888.519585902
Std: 283.693012809
Algorithm name: MDE_pBX - gen:500 q percentage:0.15 power mean exponent:1.5 ftol:1e-30 xtol:1e-30
Best: 441.299511744
Mean: 1258.78309009
Std: 310.698319457
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 5.28052623849e-09
Mean: 57.8463838812
Std: 84.4681292267
Algorithm name: jDE - gen:500 variant:2 self_adaptation:1 memory:0 ftol:1e-30 xtol:1e-30
Best: 0.0
Mean: 107.565721689
Std: 125.833049595
Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] memory:0 ftol:1e-30 xtol:1e-30
Best: 9.09494701773e-13
Mean: 32.8804046136
Std: 67.4355090112
Algorithm name: Simulated Annealing (Corana's) - iter:5000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 0.0297393134597
Mean: 341.474147127
Std: 189.527716147
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: 3.88572934753e-05
Mean: 1.05657403534
Std: 5.27731701303
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: 18.1512686151
Mean: 558.915377517
Std: 193.609012874
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 memory:0
Best: 1263.34768108
Mean: 2132.47906662
Std: 280.032593528
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 118.799556331
Mean: 564.524626069
Std: 183.411408451
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: 1.98991813302
Mean: 9.9178496424
Std: 5.03221380333
Algorithm name: MDE_pBX - gen:500 q percentage:0.15 power mean exponent:1.5 ftol:1e-30 xtol:1e-30
Best: 3.31295822411
Mean: 14.5214567283
Std: 5.2606117772
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 0.0239512390387
Mean: 4.51466379667
Std: 2.53802484642
Algorithm name: jDE - gen:500 variant:2 self_adaptation:1 memory:0 ftol:1e-30 xtol:1e-30
Best: 0.0
Mean: 0.978401009867
Std: 1.06348223623
Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] memory:0 ftol:1e-30 xtol:1e-30
Best: 0.0
Mean: 3.62376795238e-15
Std: 4.08916572771e-14
Algorithm name: Simulated Annealing (Corana's) - iter:5000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 1.03245387932
Mean: 4.58144249744
Std: 2.0303006146
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: 0.000140337233816
Mean: 1.35105834571
Std: 0.858320443568
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: 0.479753679572
Mean: 2.16060626488
Std: 1.01645535577
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 memory:0
Best: 2.98487717128
Mean: 12.8797293879
Std: 6.43206575524
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 1.02521492985
Mean: 5.96215088245
Std: 3.07911509344
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: 0.00601654933709
Mean: 12.6745752851
Std: 23.8725174777
Algorithm name: MDE_pBX - gen:500 q percentage:0.15 power mean exponent:1.5 ftol:1e-30 xtol:1e-30
Best: 10.0763507004
Mean: 3256.0438346
Std: 7088.5287686
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 0.000737458517306
Mean: 4.50448436316
Std: 1.85197245911
Algorithm name: jDE - gen:500 variant:2 self_adaptation:1 memory:0 ftol:1e-30 xtol:1e-30
Best: 0.000975524237767
Mean: 6.80343999246
Std: 16.1362543314
Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] memory:0 ftol:1e-30 xtol:1e-30
Best: 4.28636960984
Mean: 6.289128061
Std: 0.531063735644
Algorithm name: Simulated Annealing (Corana's) - iter:5000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 0.0143385225538
Mean: 7.64107781628
Std: 21.8420821744
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: 2.06546573515
Mean: 29.8946925863
Std: 31.4545735214
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: 2.74771371033
Mean: 74.5017374415
Std: 134.358375403
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 memory:0
Best: 1.10801812447e-15
Mean: 0.593786617021
Std: 1.26208595877
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 0.475051875568
Mean: 13.6123655619
Std: 16.045044465
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: 2.47637825801e-08
Mean: 0.358754911518
Std: 1.52286958008
Algorithm name: MDE_pBX - gen:500 q percentage:0.15 power mean exponent:1.5 ftol:1e-30 xtol:1e-30
Best: 1.76407755114
Mean: 8.10320401219
Std: 2.89665676388
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 2.7349766758e-06
Mean: 0.0346824008522
Std: 0.19704866056
Algorithm name: jDE - gen:500 variant:2 self_adaptation:1 memory:0 ftol:1e-30 xtol:1e-30
Best: 2.57263099712e-10
Mean: 0.471817650223
Std: 0.809422641969
Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] memory:0 ftol:1e-30 xtol:1e-30
Best: 3.99680288865e-15
Mean: 2.60852672795e-12
Std: 1.45455467743e-11
Algorithm name: Simulated Annealing (Corana's) - iter:5000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 0.0242413058679
Mean: 0.084700252137
Std: 0.0286608715182
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: 0.000825038673338
Mean: 0.0231509070209
Std: 0.125625670203
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: 0.194144163962
Mean: 0.935840359245
Std: 0.274274200409
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 memory:0
Best: 7.54951656745e-15
Mean: 0.0231029700544
Std: 0.161720790379
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 0.000101099673281
Mean: 0.479207441185
Std: 0.686220831547
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: 0.00739604033463
Mean: 0.0824595126869
Std: 0.0479684151012
Algorithm name: MDE_pBX - gen:500 q percentage:0.15 power mean exponent:1.5 ftol:1e-30 xtol:1e-30
Best: 0.533778984165
Mean: 6.780264194
Std: 6.15678598776
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 0.000437168072037
Mean: 0.171649709821
Std: 0.0919292442706
Algorithm name: jDE - gen:500 variant:2 self_adaptation:1 memory:0 ftol:1e-30 xtol:1e-30
Best: 2.88657986403e-15
Mean: 0.0354744362343
Std: 0.102360825077
Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] memory:0 ftol:1e-30 xtol:1e-30
Best: 0.0
Mean: 1.18916763112e-05
Std: 9.67347144451e-05
Algorithm name: Simulated Annealing (Corana's) - iter:5000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 0.105796585354
Mean: 0.287103040077
Std: 0.102188082672
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: 6.29557815409e-05
Mean: 0.0511155762524
Std: 0.0356571435367
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: 0.225574897479
Mean: 0.859870344766
Std: 0.195202887316
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 memory:0
Best: 0.0
Mean: 0.00901359478646
Std: 0.00882135170444
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 0.000701097317695
Mean: 0.179595476718
Std: 0.158836453741
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: -4316.87158004
Mean: -3200.80561369
Std: 624.340560577
Algorithm name: MDE_pBX - gen:500 q percentage:0.15 power mean exponent:1.5 ftol:1e-30 xtol:1e-30
Best: -3834.60710672
Mean: -1403.00811657
Std: 1015.41943025
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: -4253.85243747
Mean: -2664.22212062
Std: 564.223311432
Algorithm name: jDE - gen:500 variant:2 self_adaptation:1 memory:0 ftol:1e-30 xtol:1e-30
Best: -4411.52297561
Mean: -4268.30388545
Std: 117.970145835
Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] memory:0 ftol:1e-30 xtol:1e-30
Best: -4411.51950151
Mean: -4146.01552094
Std: 239.031845991
Algorithm name: Simulated Annealing (Corana's) - iter:5000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: -4338.87966995
Mean: -3610.68592548
Std: 416.468547975
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: -4373.39580347
Mean: -3719.08962061
Std: 430.953811631
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: -3731.24156812
Mean: -2735.81239682
Std: 506.774658177
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 memory:0
Best: -3672.2060151
Mean: -1751.76168757
Std: 656.551245798
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: -3823.34376772
Mean: -2538.25844285
Std: 541.779821936
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: 5.36481334606
Mean: 15.111165869
Std: 5.52907443545
Algorithm name: MDE_pBX - gen:500 q percentage:0.15 power mean exponent:1.5 ftol:1e-30 xtol:1e-30
Best: 5.85104344612
Mean: 21.5379263248
Std: 7.29154989673
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 4.93892454777
Mean: 12.1672743511
Std: 3.96417684383
Algorithm name: jDE - gen:500 variant:2 self_adaptation:1 memory:0 ftol:1e-30 xtol:1e-30
Best: 5.14447362566
Mean: 11.6383573147
Std: 3.96781384155
Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] memory:0 ftol:1e-30 xtol:1e-30
Best: 5.48101589858
Mean: 12.6566927796
Std: 4.02806734642
Algorithm name: Simulated Annealing (Corana's) - iter:5000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 5.14460225687
Mean: 22.1160538849
Std: 13.9841209192
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: 5.40607420644
Mean: 11.5994906604
Std: 4.23929648577
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: 5.86559661202
Mean: 37.874568689
Std: 23.251884513
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 memory:0
Best: 5.30342238424
Mean: 16.1069262872
Std: 3.9481433163
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 6.48026855394
Mean: 15.1704144179
Std: 4.11326624922
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: -1090273.70029
Mean: -300516.321158
Std: 289261.25314
Algorithm name: MDE_pBX - gen:500 q percentage:0.15 power mean exponent:1.5 ftol:1e-30 xtol:1e-30
Best: -901285.354146
Mean: -166701.934181
Std: 210011.698116
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: -1033445.99455
Mean: -200362.679126
Std: 154413.414656
Algorithm name: jDE - gen:500 variant:2 self_adaptation:1 memory:0 ftol:1e-30 xtol:1e-30
Best: -866831.663366
Mean: -276740.775929
Std: 195518.96103
Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] memory:0 ftol:1e-30 xtol:1e-30
Best: -797546.110669
Mean: -312560.279329
Std: 167244.523047
Algorithm name: Simulated Annealing (Corana's) - iter:5000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: -842748.126807
Mean: -114966.166853
Std: 193822.777651
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: -1338352.6581
Mean: -591056.819431
Std: 260006.582889
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: -598357.226387
Mean: -55631.3149476
Std: 112599.293426
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 memory:0
Best: -961774.524907
Mean: -92222.7178635
Std: 159304.498286
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: -802981.932069
Mean: -95808.3600323
Std: 112939.607526
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: 11.7405081036
Mean: 25.8823559703
Std: 5.47186733793
Algorithm name: MDE_pBX - gen:500 q percentage:0.15 power mean exponent:1.5 ftol:1e-30 xtol:1e-30
Best: 25.7509001035
Mean: 35.959667783
Std: 5.708565468
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 23.2475054875
Mean: 31.2185261947
Std: 2.97188948656
Algorithm name: jDE - gen:500 variant:2 self_adaptation:1 memory:0 ftol:1e-30 xtol:1e-30
Best: 15.7979503258
Mean: 28.0661131297
Std: 3.42227632173
Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] memory:0 ftol:1e-30 xtol:1e-30
Best: 15.1826789852
Mean: 26.8691499484
Std: 3.68967788285
Algorithm name: Simulated Annealing (Corana's) - iter:5000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 15.5879869637
Mean: 29.0975703845
Std: 7.53198874392
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: 14.738554373
Mean: 24.8324694139
Std: 3.78441029155
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: 19.7027814009
Mean: 37.8519907198
Std: 10.0425707738
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 memory:0
Best: 18.6843012387
Mean: 26.025061035
Std: 3.66287638295
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 17.8130161578
Mean: 32.7034180148
Std: 6.19427983066
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: 11.7262371024
Mean: 22.9738562893
Std: 5.12497119356
Algorithm name: MDE_pBX - gen:500 q percentage:0.15 power mean exponent:1.5 ftol:1e-30 xtol:1e-30
Best: 15.6186397914
Mean: 31.8420952018
Std: 6.99057194095
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 22.3137737675
Mean: 32.6606504212
Std: 4.90847928355
Algorithm name: jDE - gen:500 variant:2 self_adaptation:1 memory:0 ftol:1e-30 xtol:1e-30
Best: 18.6708513815
Mean: 29.8476929372
Std: 4.41933902979
Algorithm name: DE - 1220 - gen:500 self_adaptation:1 variants:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10] memory:0 ftol:1e-30 xtol:1e-30
Best: 16.7460293059
Mean: 27.4168427507
Std: 4.08452441533
Algorithm name: Simulated Annealing (Corana's) - iter:5000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 13.2253322858
Mean: 31.3024772716
Std: 10.6857717046
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: 13.4385967519
Mean: 24.8509269061
Std: 6.34800239581
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: 18.6374219486
Mean: 40.0035198676
Std: 11.5242873543
Algorithm name: CMAES - gen:500 cc:-1 cs:-1 c1:-1 cmu:-1 sigma0:0.5 ftol:1e-30 xtol:1e-30 memory:0
Best: 14.8274534081
Mean: 25.418839487
Std: 5.26975079059
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 20.266122363
Mean: 34.8662573432
Std: 7.05239717966