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Table 4 Optimal solution for coil spring problem

From: Modified differential evolution algorithm with onlooker bee operator for mixed discrete-continuous optimization

 

Branch-Bound

GA

Meta-GA

DE/rand

This article: \(\cdot\) / \(\cdot\) / 1

 

Sandgren (1990)

Chen and Tsao (1993)

Wu and Chow (1995)

Lampinen and Zelinka (1999)

DE/best

mDEOB/best

DE/cur_to_best

mDEOB/cur_to_best

\(x_1\)

10

9

9

9

9

9

9

10

\(x_2\)

1.180701

1.2287

1.227411

1.223041

1.22304

1.22304

1.22304

1.18104

\(x_3\)

0.283

0.283

0.283

0.283

0.283

0.283

0.283

0.283

\(g_1\)

54309

415.969

550.993

1008.8114

1006.92

1006.93

1006.93

5389.66

\(g_2\)

8.8187

8.9207

8.9624

8.94564

8.94562

8.94562

8.94562

8.64751

\(g_3\)

0.08298

0.08300

0.08300

0.083000

0.08300

0.08300

0.08300

0.08300

\(g_4\)

1.8193

1.7713

1.7726

1.77696

1.77696

1.77696

1.77696

1.81896

\(g_5\)

1.1723

1.3417

1.3371

1.32170

1.32170

1.32170

1.32170

1.17330

\(g_6\)

5.4643

5.4568

5.4585

5.46429

5.46427

5.46427

5.46427

5.46398

\(g_7\)

0.0

0.0

0.0

2.68 × 10−16

0.0

0.0

0.0

0.0

\(g_8\)

0.0

00174

0.0134

5.08 × 10−16

2.34 × 10−7

2.76 × 10−9

9.61 × 10−8

6.71 × 10−4

f(x)

2.7995

2.6709

2.6681

2.65856

2.65856

2.65856

2.65856

2.65856

S.A.

95.0%

69.0%

88.0%

90.0%

95.0%

  1. ‘S.A.’ is the percentage in multiple runs of successfully achieving the optimal value