TY  - JOUR
TI  - A novel hybrid global optimization algorithm having training strategy: hybrid
Taguchi-vortex search algorithm
AB  - In this paper, a novel hybrid Taguchi-vortex search algorithm (HTVS) is proposed for solving global
optimization problems. Taguchi orthogonal approximation and vortex search algorithm (VS) are hybridized in presenting
method. In HTVS, orthogonal arrays in the Taguchi method are trained and obtained better solutions are used to find
global optima in VS. Thus, HTVS has better relation between exploration and exploitation, and it exhibits more powerful
approximation to find global optimum value. Proposed HTVS algorithm is applied to sixteen well-known benchmark
optimization test functions with different dimensions. The results are compared with the Taguchi orthogonal array
approximation (TOAA), vortex search algorithm, grey wolf optimizer (GWO), sine cosine algorithm (SCA), moth-flame
optimization algorithm (MFO), whale optimization algorithm (WOA) and salp swarm algorithm (SSA). In order to
compare the effectiveness of HTVS statistically, Wilcoxon signed-rank test (WSRT) is used in this study. Furthermore,
HTVS is applied to two different real engineering problems having some constraints (tension/compression spring design
and pressure vessel design). All obtained results suggested that HTVS can find optimal or very close to optimal results.
Moreover, it has good computational ability and fast convergence behavior as well.
AU  - ÇOBAN, Melih
AU  - TEZCAN, Süleyman Sungur
AU  - TAPLAMACIOĞLU, Müslüm Cengiz
AU  - SAKA, Mustafa
AU  - EKE, İbrahim
DO  - 10.3906/elk-2004-193
PY  - 2021
JO  - Turkish Journal of Electrical Engineering and Computer Sciences
VL  - 29
IS  - 4
SN  - 1300-0632
SP  - 1908
EP  - 1928
DB  - TRDizin
UR  - http://search/yayin/detay/523774
ER  -