General Information
- Model file: C:\Users\walther\Documents\SEP5848_Pós_2023\09_10_2023_Ponte_1\4_5_Tecelagem_Godoy_Crane.spp
- GAWizard: .Models.Godoy.Godoy.GAWizard
- Generated on: 2023/10/12 20:50:12.7800
- Running time of the optimization: 21:01.2780
Model
Optimization results
Best Fitness: 18:13:00.0000The parameters of the best solution are set in the model.
Fitness calculation
Fitness calculation by a weighted sum| Target value | Weighting |
|---|---|
| root.totalSetupTime | 1.00000 |
| root.totalSetupTime_1 | 1.00000 |
| root.Fitness_Value | 1.00000 |
Calculation of the fitness values of the best solution
| Fitness | root.totalSetupTime | root.totalSetupTime_1 | root.Fitness_Value |
|---|---|---|---|
| 18:13:00.0000 | 7:54:00.0000 | 36840 | 5:00.0000 |
| 18:13:00.0000 | 7:54:00.0000 | 36840 | 5:00.0000 |
| 18:13:00.0000 | 7:54:00.0000 | 36840 | 5:00.0000 |
| 18:13:00.0000 | 7:54:00.0000 | 36840 | 5:00.0000 |
| 18:13:00.0000 | 7:54:00.0000 | 36840 | 5:00.0000 |
| 18:13:00.0000 | 7:54:00.0000 | 36840 | 5:00.0000 |
| 18:13:00.0000 | 7:54:00.0000 | 36840 | 5:00.0000 |
| 18:13:00.0000 | 7:54:00.0000 | 36840 | 5:00.0000 |
| 18:13:00.0000 | 7:54:00.0000 | 36840 | 5:00.0000 |
| 18:13:00.0000 | 7:54:00.0000 | 36840 | 5:00.0000 |
Best parameter of the allocation problems
root.Buffer.Capacity: 14
Best solutions of the sequence problems
.Models.Godoy.Godoy.tf_dados
42, 14, 8, 52, 22, 11, 37, 9, 48, 40, 63, 13, 57, 60, 27, 20, 51, 67, 50, 26, 18, 66, 10, 43, 31, 45, 17, 64, 46, 41, 58, 28, 16, 2, 4, 49, 65, 12, 25, 29, 44, 59, 56, 68, 36, 30, 33, 55, 3, 32, 24, 54, 23, 61, 53, 1, 47, 21, 6, 38, 7, 5, 34, 35, 62, 39, 19, 15
.Models.Godoy.Godoy.tf_dados_1
20, 71, 29, 106, 40, 6, 161, 18, 52, 63, 25, 17, 35, 109, 138, 126, 166, 67, 93, 51, 160, 69, 36, 19, 85, 154, 103, 32, 91, 55, 73, 47, 41, 33, 125, 68, 140, 3, 141, 112, 12, 26, 72, 61, 119, 148, 94, 163, 88, 13, 5, 65, 117, 14, 131, 76, 150, 121, 123, 165, 111, 56, 58, 156, 137, 149, 164, 108, 48, 124, 102, 64, 132, 97, 100, 77, 87, 60, 157, 83, 79, 54, 116, 153, 101, 159, 133, 113, 4, 37, 31, 44, 16, 2, 27, 104, 28, 114, 84, 82, 128, 62, 11, 115, 81, 89, 59, 42, 110, 75, 57, 162, 34, 45, 122, 105, 30, 139, 24, 167, 142, 130, 127, 22, 43, 53, 107, 145, 38, 146, 86, 49, 95, 134, 15, 158, 7, 1, 39, 144, 10, 80, 50, 155, 152, 120, 21, 70, 8, 96, 99, 74, 78, 151, 143, 98, 118, 92, 23, 136, 168, 129, 66, 90, 46, 9, 147, 135
Evolution of the fitness values of the generations
Settings
Definition of optimization parameter
| Parameter: | root.tf_dados |
|---|---|
| Sequence of | root.tf_dados |
| 68 Elements | |
| Parameter: | root.tf_dados_1 |
|---|---|
| Sequence of | root.tf_dados_1 |
| 168 Elements | |
| Parameter: | root.Buffer.Capacity |
|---|---|
| Lower bound | 10 |
| Upper bound | 20 |
| Increment | 4 |
Settings of the Genetic Algorithm
Direction of the Optimization: MinimumNumber of Generations: 8
Size of Generation: 15
Observations per individual: 10
Generated individuals
The Genetic Algorithm generated 225 individuals.The search for equal individuals is performed.
Number of multiple generated individuals: 2
The penalty method was not applied.
Number of evaluated individuals: 223
Observations per individual: 10
2230 simulation runs are performed.
Children of all generations
Children of all generations with Min-Max intervals of 10 observationsGeneration 1
Generation 2
Generation 3
Generation 4
Generation 5
Generation 6
Generation 7
Generation 8
