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Test Data (1304_50_2)
magnific0 edited this page Feb 25, 2014
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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: 8.18545231596e-12
Mean: 441.241139881
Std: 207.028115277
Algorithm name: MDE_pBX - gen:500 q percentage:0.15 power mean exponent:1.5 ftol:1e-30 xtol:1e-30
Best: 0.0
Mean: 176.198734226
Std: 137.979813071
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 0.000227950547924
Mean: 0.00597766074757
Std: 0.00714369370629
Algorithm name: jDE - gen:500 variant:2 self_adaptation:1 memory:0 ftol:1e-30 xtol:1e-30
Best: 0.0
Mean: 4.50199877378e-13
Std: 4.5472461295e-13
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: 2.36468622461e-11
Mean: 2.86944577965e-07
Std: 2.62553040906e-06
Algorithm name: Simulated Annealing (Corana's) - iter:25000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 0.0248405695265
Mean: 226.957493461
Std: 153.409697229
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: 2.0695177227e-05
Mean: 5.35658185345e-05
Std: 1.52442347719e-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: 119.251527112
Mean: 424.928641147
Std: 166.966484461
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: 991.243826955
Mean: 1922.33791458
Std: 256.166801178
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 0.0594396057659
Mean: 110.556280073
Std: 73.5434766471
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: 0.994959057102
Mean: 4.43074905617
Std: 1.78091720878
Algorithm name: MDE_pBX - gen:500 q percentage:0.15 power mean exponent:1.5 ftol:1e-30 xtol:1e-30
Best: 0.0
Mean: 1.43536041969
Std: 1.06559953293
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 1.80011241929
Mean: 5.4299976502
Std: 1.48027020175
Algorithm name: jDE - gen:500 variant:2 self_adaptation:1 memory:0 ftol:1e-30 xtol:1e-30
Best: 0.0
Mean: 2.1955770535e-14
Std: 3.64196648559e-14
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: 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: 0.029546121725
Mean: 5.14048348487
Std: 2.16236371884
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: 2.44280325035e-06
Mean: 0.00143762956798
Std: 0.0167309275399
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: 0.0902641087329
Mean: 0.51430765347
Std: 0.314535222538
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: 3.20376796233
Std: 1.52251444757
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 0.000209815040463
Mean: 0.138942308086
Std: 0.268358328081
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: 0.00283336905965
Mean: 3.59992552131
Std: 1.64783546803
Algorithm name: MDE_pBX - gen:500 q percentage:0.15 power mean exponent:1.5 ftol:1e-30 xtol:1e-30
Best: 0.620918082788
Mean: 10.4346663577
Std: 12.3237535609
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 0.292957419495
Mean: 1.18747602196
Std: 0.405070682811
Algorithm name: jDE - gen:500 variant:2 self_adaptation:1 memory:0 ftol:1e-30 xtol:1e-30
Best: 8.30941279595e-05
Mean: 2.29931006141
Std: 1.55614869644
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: 4.16977987702
Mean: 5.61146976203
Std: 0.326340015614
Algorithm name: Simulated Annealing (Corana's) - iter:25000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 0.024036677332
Mean: 2.08876889397
Std: 3.94327070651
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: 5.59518334966
Mean: 11.3242603906
Std: 13.5089825269
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: 1.36498707032
Mean: 32.4681644351
Std: 49.482459537
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: 4.32394383674e-29
Mean: 1.32878750734e-28
Std: 4.9880726235e-29
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 0.115715223917
Mean: 1.3188449009
Std: 0.770891675796
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: 2.50427132364e-08
Mean: 1.79394275026e-07
Std: 1.27765601239e-07
Algorithm name: MDE_pBX - gen:500 q percentage:0.15 power mean exponent:1.5 ftol:1e-30 xtol:1e-30
Best: 3.99680288865e-15
Mean: 9.96319187277e-05
Std: 0.000994107797716
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 0.000120903029896
Mean: 0.000384501539769
Std: 0.000131151011831
Algorithm name: jDE - gen:500 variant:2 self_adaptation:1 memory:0 ftol:1e-30 xtol:1e-30
Best: 1.80741199785e-10
Mean: 8.15204366234e-10
Std: 3.90565501522e-10
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: 2.36328290271e-12
Std: 1.72063816678e-11
Algorithm name: Simulated Annealing (Corana's) - iter:25000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 0.0221151067267
Mean: 0.0860092713758
Std: 0.0285027132312
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: 0.00064798397175
Mean: 0.00116421251448
Std: 0.000185594846695
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: 0.102963449809
Mean: 0.353859526822
Std: 0.140590232031
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: 3.99680288865e-15
Mean: 1.75859327101e-14
Std: 5.38589958324e-14
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 7.22506896946e-05
Mean: 0.00175367860653
Std: 0.0013132558737
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: 3.10610259735e-09
Mean: 0.03545310174
Std: 0.0190560778138
Algorithm name: MDE_pBX - gen:500 q percentage:0.15 power mean exponent:1.5 ftol:1e-30 xtol:1e-30
Best: 0.0
Mean: 0.0164534305188
Std: 0.0146211037544
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 0.083354389848
Mean: 0.221104302686
Std: 0.0483848358818
Algorithm name: jDE - gen:500 variant:2 self_adaptation:1 memory:0 ftol:1e-30 xtol:1e-30
Best: 1.29220079081e-10
Mean: 0.00112263267391
Std: 0.00221131245382
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: 1.5782770868e-09
Std: 1.86386679038e-08
Algorithm name: Simulated Annealing (Corana's) - iter:25000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 0.0764439252872
Mean: 0.336331379737
Std: 0.130620366385
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: 3.36220431838e-05
Mean: 0.00899038463572
Std: 0.00769287479254
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: 0.238029207421
Mean: 0.761524459944
Std: 0.251766635614
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: 0.00041902690218
Std: 0.00184628817652
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 6.72652206158e-05
Mean: 0.0152573594013
Std: 0.0110521476056
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: -4341.91799465
Mean: -3860.443213
Std: 352.217379727
Algorithm name: MDE_pBX - gen:500 q percentage:0.15 power mean exponent:1.5 ftol:1e-30 xtol:1e-30
Best: -4411.52297573
Mean: -4284.11082293
Std: 135.745850021
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: -3708.54697714
Mean: -2743.75677591
Std: 290.796243978
Algorithm name: jDE - gen:500 variant:2 self_adaptation:1 memory:0 ftol:1e-30 xtol:1e-30
Best: -4411.52139799
Mean: -4382.02803611
Std: 27.4261957397
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: -4409.04372996
Mean: -4336.04349573
Std: 49.6402384565
Algorithm name: Simulated Annealing (Corana's) - iter:25000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: -4253.59554678
Mean: -3517.9219475
Std: 393.968605655
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: -4411.48456236
Mean: -4354.04831984
Std: 113.829038214
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: -4242.40903798
Mean: -3678.26565052
Std: 404.121745146
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: -4411.52297573
Mean: -3299.08610833
Std: 569.18386965
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: -4340.87256211
Mean: -3941.76800369
Std: 195.574261348
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: 5.10012191283
Mean: 10.1217611559
Std: 3.04846242334
Algorithm name: MDE_pBX - gen:500 q percentage:0.15 power mean exponent:1.5 ftol:1e-30 xtol:1e-30
Best: 4.93077996086
Mean: 11.7553254193
Std: 3.39588037167
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 5.30345470606
Mean: 6.39468015875
Std: 2.25429939222
Algorithm name: jDE - gen:500 variant:2 self_adaptation:1 memory:0 ftol:1e-30 xtol:1e-30
Best: 5.30357422756
Mean: 6.80939692571
Std: 2.3013483864
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: 5.60232064502
Mean: 8.03530850703
Std: 2.08001433077
Algorithm name: Simulated Annealing (Corana's) - iter:25000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 4.98283763134
Mean: 17.4817537346
Std: 9.88589638454
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: 5.33101033288
Mean: 8.39561985418
Std: 3.72697573176
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: 5.57113539142
Mean: 19.1473993515
Std: 10.2013287508
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: 10.5408242849
Mean: 16.0143891179
Std: 1.66630511677
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 5.82576399743
Mean: 10.7085554792
Std: 2.51688144605
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: -1307494.6894
Mean: -628257.614647
Std: 218276.995724
Algorithm name: MDE_pBX - gen:500 q percentage:0.15 power mean exponent:1.5 ftol:1e-30 xtol:1e-30
Best: -1449719.58208
Mean: -729452.418911
Std: 232983.666964
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: -748945.277413
Mean: -350819.361698
Std: 121434.208603
Algorithm name: jDE - gen:500 variant:2 self_adaptation:1 memory:0 ftol:1e-30 xtol:1e-30
Best: -969557.135918
Mean: -508671.749039
Std: 141474.739699
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: -924661.196419
Mean: -552494.476207
Std: 142148.271093
Algorithm name: Simulated Annealing (Corana's) - iter:25000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: -1071501.85872
Mean: -105712.631631
Std: 175102.438946
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: -1401434.86993
Mean: -787658.407352
Std: 183314.490381
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: -930127.54697
Mean: -129611.224606
Std: 186231.089421
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: -1531113.46856
Mean: -151344.195341
Std: 245118.344612
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: -905056.327177
Mean: -358577.002927
Std: 175740.742849
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: 10.8563166107
Mean: 20.5761898197
Std: 2.82219302135
Algorithm name: MDE_pBX - gen:500 q percentage:0.15 power mean exponent:1.5 ftol:1e-30 xtol:1e-30
Best: 17.0568767134
Mean: 23.5748765846
Std: 2.00910326397
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 19.8367335
Mean: 27.9405306156
Std: 2.28412501563
Algorithm name: jDE - gen:500 variant:2 self_adaptation:1 memory:0 ftol:1e-30 xtol:1e-30
Best: 15.8277134281
Mean: 24.0208023419
Std: 2.50626435803
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: 14.6012712458
Mean: 22.262307354
Std: 2.67823728143
Algorithm name: Simulated Annealing (Corana's) - iter:25000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 9.56066954748
Mean: 23.7508435899
Std: 6.25755720594
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: 13.5113967182
Mean: 24.0341881142
Std: 3.52306897202
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: 15.5284010844
Mean: 28.2534881008
Std: 5.34980388354
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: 14.2726343379
Mean: 21.0909304741
Std: 2.52375520857
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 15.2249252953
Mean: 24.6420615906
Std: 3.37730624402
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: 9.8050226739
Mean: 17.4574244123
Std: 2.25594518732
Algorithm name: MDE_pBX - gen:500 q percentage:0.15 power mean exponent:1.5 ftol:1e-30 xtol:1e-30
Best: 14.080417822
Mean: 17.3503409285
Std: 1.87630951598
Algorithm name: Differential Evolution - gen:500 F: 0.8 CR: 0.9 variant:2 ftol:1e-30 xtol:1e-30
Best: 16.3456016887
Mean: 27.8112356076
Std: 3.29023016907
Algorithm name: jDE - gen:500 variant:2 self_adaptation:1 memory:0 ftol:1e-30 xtol:1e-30
Best: 15.0354491116
Mean: 23.959011312
Std: 2.76710586207
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: 10.92461888
Mean: 22.3185680192
Std: 3.03817567545
Algorithm name: Simulated Annealing (Corana's) - iter:25000 Ts:1 Tf:0.01 steps:1 bin_size:20 range:1
Best: 5.88397368957
Mean: 21.232946987
Std: 7.19911917943
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: 15.7754185485
Mean: 21.6182299787
Std: 3.05732371983
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: 12.6919450296
Mean: 25.6734619829
Std: 6.95456312657
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: 11.8129964274
Mean: 15.4799135715
Std: 1.55850155068
Algorithm name: Artificial Bee Colony optimization - gen:250 limit:20
Best: 17.1863463429
Mean: 26.7273458823
Std: 3.7406610432