Skip to main content

Table 13 Optimum results for tension/compression spring 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
d(\({x}_{1}\)) D(\({x}_{2}\)) N(\({x}_{3}\))
GSA 0.050276 0.323680 13.525410 0.012702
CPSO 0.051728 0.357644 11.244543 0.012674
CDE 0.051609 0.354714 11.410831 0.012670
SCA 0.052160 368,159 10.648442 0.012669
EO 0.0516199100 0.355054381 11.387967 0.012666
PSOSCANMS 0.05072 0.334801 10.79431 0.012475
PSO 0.051728 0.357644 11.244543 0.0126747
HS 0.051154 0.349871 12.076432 0.0126706
DE 0.051609 0.354714 11.410831 0.0126702
AFA 5.167E−02 3.562E−01 1.132E+01 0.012624
GWO 0.05169 0.356737 11.28885 0.012666
WCA 0.0517208702 0.3579276279 11.1912042488 0.012630231
Modified DE 0.051688 0.356692 11.290483 0.012665
QPSO 0.051515 0.352529 11.538862 0.012665
SHO 0.051144 0.343751 12.0955 0.012674000
HS 0.05025 0.316351 15.23960 0.012776352
EPO 0.051087 0.342908 12.0898 0.012656987
aDE 0.05012 0.328431 11.49631 0.012552
aPSO 0.05012 0.328431 11.49631 0.012568
haDEPSO 0.05012 0.328431 11.49631 0.012475