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Table 11 Optimum results for speed reducer design problem

From: An advanced hybrid meta-heuristic algorithm for solving small- and large-scale engineering design optimization problems

Algorithms Optimal values for variables Optimal cost
b m p ll l2 d1 d2
EPO 3.50123 0.7 17 7.3 7.8 3.33421 5.26536 2994.2472
SHO 3.50159 0.7 17 7.3 7.8 3.35127 5.28874 2998.5507
PSO 3.500019 0.7 17 8.3 7.8 3.352412 5.286715 3005.763
MVO 3.508502 0.7 17 7.3 7.8 3.358073 5.286777 3002.928
SCA 3.508755 0.7 17 7.3 7.8 3.461020 5.289213 3030.563
GSA 3.600000 0.7 17 8.3 7.8 3.369658 5.289224 3051.120
GA 3.510253 0.7 17 8.35 7.8 3.362201 5.287723 3067.561
HS 3.520124 0.7 17 8.37 7.8 3.366970 5.288719 3029.002
GWO 3.506690 0.7 17 7.380933 7.815726 3.357847 5.286768 3001.288
AFA 3.500 0.700 0.700e+00 7.3027 7.8007 3.350 5.287 3027.354
MBA [32] 3.500 0.700 0.700e+00 7.3007 7.716 3.350 5.287 3077.426
CS 3.501 0.700 0.700e+00 7.6057 7.818 3.352 5.287 3052.128
KH 3.500 0.700 0.700e+00 7.3667 7.823 3.350 5.287 3029.543
aDE 3.500 0.7 17 7.3809 7.8 3.350 5.289 2992.1242
aPSO 3.500 0.7 17 7.3809 7.8 3.350 5.289 2994.2442
haDEPSO 3.500 0.7 17 7.3809 7.8 3.350 5.289 2990.3582