Review of the grey wolf optimization algorithm: variants and applications

Author:

Liu YunyunORCID,As’arry Azizan,Hassan Mohd Khair,Hairuddin Abdul Aziz,Mohamad Hesham

Funder

GP-IPM

FRGS

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Reference134 articles.

1. Amr HA, Khajehzadeh M, Taha M, Beheshti Z, Mariyam S, and Shamsuddin H, “A review of population-based meta-heuristic algorithm,” 2013. [Online]. Available: www.i-csrs.org

2. Mirjalili S, Mirjalili SM, Lewis A (2014) Grey wolf optimizer. Adv Eng Softw 69:46–61. https://doi.org/10.1016/j.advengsoft.2013.12.007

3. Institute of Electrical and Electronics Engineers (2008) In: IEEE World Congress on Computational Intelligence (2008: Hong Kong, Evolutionary Computation, 2008, CEC 2008, (IEEE World Congress on Computational Intelligence), IEEE Congress on: date, 1–6 June, 2008

4. Lin L, Gen M (2009) Auto-tuning strategy for evolutionary algorithms: balancing between exploration and exploitation. Soft Comput. https://doi.org/10.1007/s00500-008-0303-2

5. Kirkpatrick S, Gelatt CD, and Vecchi MP (1983) Optimization by Simulated Annealing. [Online]. Available: https://www.science.org

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