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E. Uray, H. Hakli, S. Carbas, “Statistical investigation of the robustness for the optimization algorithms,” Nature-Inspired Metaheuristic Algorithms for Engineering Optimization Applications, pp. 201–224, 2021.Search in Google Scholar
G. Joy, C. Huyck, X.S. Yang, “Review of Parameter Tuning Methods for Nature-Inspired Algorithms,” Benchmarks and Hybrid Algorithms in Optimization and Applications, pp. 33–47, 2023.Search in Google Scholar
M. Dubey, V. Kumar, M. Kaur, T.P. Dao, “A systematic review on harmony search algorithm: theory, literature, and applications,” Mathematical Problems in Engineering, pp. 1–22, 2021.Search in Google Scholar
S. Mirjalili and A. Lewis, “The whale optimization algorithm,” Advances in Engineering Software, vol. 95, pp. 51–67, 2016.Search in Google Scholar
M.H. Nadimi-Shahraki, H. Zamani, Z.A. Varzaneh, S. Mirjalili, “A Systematic Review of the Whale Optimization Algorithm: Theoretical Foundation, Improvements, and Hybridizations,” Archives of Computational Methods in Engineering, pp. 1–47, 2023.Search in Google Scholar
K. Lu, Z. Ma, “A modified whale optimization algorithm for parameter estimation of software reliability growth models,” Journal of Algorithms & Computational Technology, vol. 15, pp. 17483026211034442, 2021.Search in Google Scholar
R.A.F.I.D. Sagban, “Reactive approach for automating exploration and exploitation in ant colony optimization,” doctoral dissertation, Universiti Utara Malaysia, Malaysia, 2016.Search in Google Scholar
F. Hutter, H.H. Hoos, T. Stützle, “Automatic algorithm configuration based on local search,” AAAI, vol. 7, pp. 1152–1157, 2007.Search in Google Scholar
M. Birattari, J. Kacprzyk, Tuning metaheuristics: a machine learning perspective, vol. 197. Berlin: Springer, 2009.Search in Google Scholar
Duque, D.A. Múnera, D. Diaz, S. Abreu, “Solving QAP with Auto-parameterization in Parallel Hybrid Metaheuristics,” International Conference on Optimization and Learning, pp. 294–309, Cham, Springer International Publishing, 2021.Search in Google Scholar
E. Uray, S. Carbas, Z.W. Geem, S. Kim, “Parameters optimization of Taguchi method integrated hybrid harmony search algorithm for engineering design problems,” Mathematics, vol. 10, no. 3, p. 327, 2022.Search in Google Scholar
A.J. Haleel, L.M. Dawood, “Binary Pareto Multi-Objective Whale Optimization Algorithm for Power Plant Maintenance Scheduling,” Iraqi Journal of Computers, Communications, Control and Systems Engineering, 2024, (In Press).Search in Google Scholar
A.C.K. Ferrari, G.V. Leandro, L. dos Santos Coelho, C.A.G. da Silva, E.G. de Lima, C. R. Chaves, “Tuning of control parameters of grey wolf optimizer using fuzzy inference,” IEEE Latin America Transactions, vol. 17, no. 07, pp. 1191–1198, 2019.Search in Google Scholar
E. Shadkam, “Parameter setting of meta-heuristic algorithms: A new hybrid method based on DEA and RSM,” Environmental Science and Pollution Research, vol. 29, no. 15, pp. 22404–22426, 2022.Search in Google Scholar
C.G. Tan, S.S. Choong, L.P. Wong, “A machine-learningbased approach for parameter control in bee colony optimization for traveling salesman problem,” International Conference on Technologies and Applications of Artificial Intelligence (TAAI), pp. 54–59, IEEE, 2021.Search in Google Scholar
H. Wang, Q. Geng, Z. Qiao, “Parameter tuning of particle swarm optimization by using Taguchi method and its application to motor design,” 4th IEEE International Conference on Information Science and Technology, pp. 722–726, IEEE, 2014.Search in Google Scholar
S.M. Mousavi, P. Shahnazari-Shahrezaei, “Minimizing the Makespan and Total Tardiness in Hybrid Flow Shop Scheduling with Sequence-Dependent Setup Times,” Management and Production Engineering Review, vol. 14, 2023.Search in Google Scholar
H.M. Pandey, “Parameters quantification of genetic algorithm,” Information Systems Design and Intelligent Applications: Proceedings of Third International Conference INDIA 2016, Volume 2, pp. 711–719, Springer India, 2016.Search in Google Scholar
X. Jia, G. Lu, “A hybrid Taguchi binary particle swarm optimization for antenna designs,” IEEE Antennas and Wireless Propagation Letters, vol. 18, no. 8, pp. 1581–1585, 2019.Search in Google Scholar
R.K. Agrawal, B. Kaur, S. Sharma, “Quantum based whale optimization algorithm for wrapper feature selection,” Applied Soft Computing, vol. 89, p. 106092, 2020.Search in Google Scholar
Y. Cao, Y. Li, G. Zhang, K. Jermsittiparsert, M. Nasseri, “An efficient terminal voltage control for PEMFC based on an improved version of whale optimization algorithm,” Energy Reports, vol. 6, pp. 530–542, 2020.Search in Google Scholar
Q.V. Pham, S. Mirjalili, N. Kumar, M. Alazab, W.J. Hwang, “Whale optimization algorithm with applications to resource allocation in wireless networks,” IEEE Transactions on Vehicular Technology, vol. 69, no. 4, pp. 4285–4297, 2020.Search in Google Scholar
J. Wang, J. Bei, H. Song, H. Zhang, P. Zhang, “A whale optimization algorithm with combined mutation and removing similarity for global optimization and multilevel thresholding image segmentation,” Applied Soft Computing, vol. 137, p. 110130, 2023.Search in Google Scholar
T.K. Dao, T.S. Pan, J.S. Pan, “A multi-objective optimal mobile robot path planning based on whale optimization algorithm,” IEEE 13th International Conference on Signal Processing (ICSP), pp. 337–342, IEEE, 2016.Search in Google Scholar
W. Yankai, W. Shilong, L. Dong, S. Chunfeng, Y. Bo, “An improved multi-objective whale optimization algorithm for the hybrid flow shop scheduling problem considering device dynamic reconfiguration processes,” Expert Systems with Applications, vol. 174, p. 114793, 2021.Search in Google Scholar
W. Guo, T. Liu, F. Dai, P. Xu, “An improved whale optimization algorithm for forecasting water resources demand,” Applied Soft Computing, vol. 86, p. 105925, 2020.Search in Google Scholar
Y. Mousavi, A. Alfi, I.B. Kucukdemiral, “Enhanced fractional chaotic whale optimization algorithm for parameter identification of isolated wind-diesel power systems,” IEEE Access, vol. 8, pp. 140862–140875, 2020.Search in Google Scholar
T.A. Sazon, Q. Zhang, H. Nikpey, “Comparison of different configurations of a solar-assisted ground-source CO2 heat pump system for space and water heating using Taguchi-Grey Relational analysis,” Energy Conversion and Management, vol. 300, p. 117881, 2024.Search in Google Scholar
P.A. Sylajakumari, R. Ramakrishnasamy, G. Palaniappan, “Taguchi grey relational analysis for multi-response optimization of wear in co-continuous composite,” Materials, vol. 11, no. 9, pp. 1743, 2018.Search in Google Scholar
S. Jozić, D. Bajić, L. Celent, “Application of compressed cold air cooling: achieving multiple performance characteristics in end milling process,” Journal of Cleaner Production, vol. 100, pp. 325–332, 2015.Search in Google Scholar
F. Kolahan, M.A. Moghaddam, “The use of Taguchi method with grey relational analysis to optimize the EDM process parameters with multiple quality characteristics,” Scientia Iranica, vol. 22, no. 2, pp. 530–538, 2015.Search in Google Scholar
