Table 13 Performance of optimization algorithms on speed reducer design problem.

From: Bobcat Optimization Algorithm: an effective bio-inspired metaheuristic algorithm for solving supply chain optimization problems

Algorithm

Optimum variables

Optimum cost

b

M

p

l1

l2

d1

d2

BOA

3.5

0.7

17

7.3

7.8

3.3502147

5.2866832

2996.3482

CMA-ES

3.5000001

0.7

17

7.3000011

7.8

3.3502147

5.2866832

2996.3482

EBOwithCMAR

3.5

0.7

17

7.3000001

7.8

3.3502147

5.2866832

2996.3482

SPS_L_SHADE_EIG

3.5105122

0.7

17

7.4051215

7.8525608

3.3508361

5.3091074

3017.617

LSHADE_cnEpSi

3.5

0.7

17

7.3

7.8

3.3502147

5.2866832

2996.3482

LSHADE

3.5014711

0.7

17

7.3

7.8525608

3.3502518

5.2870862

2998.3472

WSO

3.5000004

0.7

17

7.3000081

7.8000003

3.3502148

5.2866833

2996.3483

AVOA

3.5

0.7

17

7.3000006

7.8

3.3502147

5.2866832

2996.3482

RSA

3.5751215

0.7

17

8.0512152

8.1756076

3.3546557

5.44693

3148.3385

MPA

3.5

0.7

17

7.3

7.8

3.3502147

5.2866832

2996.3482

TSA

3.5105126

0.7

17

7.3

8.1756076

3.3504803

5.2895627

3010.6338

WOA

3.5712923

0.7

17

7.3

7.9706109

3.3595034

5.2867424

3030.4996

GWO

3.5005226

0.7

17

7.3041919

7.8

3.3614073

5.2884166

3000.5584