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Table 4 Comparison of trained parameters along with their fitness for GA and GA-SQP algorithms in case of problem 2

From: Memetic computing through bio-inspired heuristics integration with sequential quadratic programming for nonlinear systems arising in different physical models

Method

Absolute values

\(f_{1} ({\mathbf{t}})\)

\(f_{2} ({\mathbf{t}})\)

\(f_{3} ({\mathbf{t}})\)

\(f_{4} ({\mathbf{t}})\)

\(f_{5} ({\mathbf{t}})\)

\(f_{6} ({\mathbf{t}})\)

\(f_{7} ({\mathbf{t}})\)

\(f_{8} ({\mathbf{t}})\)

\(f_{9} ({\mathbf{t}})\)

\(f_{10} ({\mathbf{t}})\)

GA-1

1.95E−04

8.59E−05

8.04E−05

6.73E−05

2.14E−06

1.99E−04

2.03E−04

5.08E−05

2.38E−05

1.28E−04

GA-2

1.11E−04

6.11E−05

1.45E−04

1.64E−05

1.59E−04

3.00E−04

9.51E−05

1.51E−04

1.06E−04

3.37E−04

GA-3

7.70E−03

2.72E−03

7.92E−03

9.06E−03

8.95E−03

8.62E−04

3.63E−03

7.65E−03

6.87E−03

2.55E−03

GA-4

1.16E−03

8.85E−04

7.90E−04

5.93E−04

2.00E−03

8.81E−04

2.61E−04

4.13E−04

8.22E−05

1.26E−03

GA-5

6.24E−05

1.51E−06

1.10E−04

1.18E−04

3.31E−05

8.62E−06

1.83E−05

3.80E−05

9.69E−05

3.09E−05

GA-6

7.95E−05

1.03E−04

6.85E−05

1.35E−04

4.90E−05

2.66E−04

2.10E−04

2.02E−04

2.03E−04

8.51E−05

GA-7

1.15E−03

1.79E−03

1.38E−03

2.72E−04

2.27E−03

3.74E−03

2.23E−03

7.52E−04

6.01E−04

2.69E−03

GA-8

1.33E−04

4.64E−04

1.22E−04

8.29E−05

9.25E−04

5.37E−05

2.72E−05

3.39E−04

7.71E−04

7.23E−04

GA-9

4.50E−04

3.23E−05

3.72E−04

3.20E−04

8.02E−05

6.25E−04

1.68E−04

2.28E−04

5.79E−05

3.10E−04

GA-10

4.43E−04

1.85E−05

4.26E−04

7.06E−05

4.04E−05

2.16E−04

1.50E−04

2.12E−04

5.02E−04

5.50E−04

GA-11

1.13E−02

1.90E−03

2.95E−03

1.00E−02

2.57E−03

6.58E−03

4.03E−03

7.04E−03

4.98E−03

7.41E−03

GA-12

1.09E−03

7.57E−04

1.41E−03

1.54E−04

1.86E−03

1.98E−03

1.13E−03

4.83E−04

1.59E−04

4.41E−03

GA-SQP-1

3.51E−17

9.63E−17

8.33E−17

1.69E−17

2.21E−17

1.09E−16

5.20E−18

3.08E−17

1.52E−16

2.47E−17

GA-SQP-2

1.46E−16

1.65E−17

2.69E−17

1.78E−17

1.44E−16

8.24E−17

5.07E−17

3.69E−17

4.24E−17

2.58E−17

GA-SQP-3

9.06E−17

7.33E−17

7.98E−17

8.24E−18

1.32E−16

2.60E−18

5.64E−17

9.02E−17

4.36E−17

2.63E−17

GA-SQP-4

2.39E−17

1.65E−17

8.76E−17

8.67E−18

3.73E−17

3.17E−17

6.29E−17

6.11E−17

1.25E−16

7.98E−17

GA-SQP-5

8.89E−17

3.73E−17

2.69E−17

6.42E−17

3.51E−17

2.65E−17

5.29E−17

6.33E−17

9.89E−17

2.92E−17

GA-SQP-6

3.34E−17

7.16E−17

8.07E−17

3.77E−17

2.34E−17

8.24E−17

1.16E−16

9.11E−18

6.90E−17

3.01E−17

GA-SQP-7

3.43E−17

1.65E−17

2.60E−17

3.73E−17

2.17E−17

5.46E−17

6.07E−17

4.77E−18

4.23E−17

8.58E−17

GA-SQP-8

3.47E−17

1.69E−17

7.98E−17

6.42E−17

2.13E−17

4.34E−19

1.15E−16

2.17E−17

9.82E−17

2.57E−17

GA-SQP-9

3.47E−17

1.65E−17

3.21E−17

4.68E−17

9.11E−17

2.60E−18

1.17E−16

6.07E−18

4.23E−17

8.03E−17

GA-SQP-10

2.21E−17

1.69E−17

1.36E−16

6.64E−17

3.25E−17

8.67E−19

5.25E−17

5.07E−17

6.79E−17

2.96E−17

GA-SQP-11

2.13E−17

9.45E−17

2.78E−17

4.60E−17

8.98E−17

2.60E−17

6.07E−17

1.86E−17

6.87E−17

8.65E−17

GA-SQP-12

1.32E−16

1.47E−17

2.08E−17

4.38E−17

3.38E−17

2.95E−17

1.73E−18

9.41E−17

1.20E−17

3.01E−17