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Research Article

Analysis of dependence of grey wolf optimizer to shift-transformations and its shift-invariant improved methods adaptively controlling the search areas

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Pages 66-79 | Received 25 Sep 2023, Accepted 22 Jan 2024, Published online: 28 Feb 2024

References

  • Mirjalili S, Mirjalili SM, Lewis A. Grey wolf optimizer. Adv Eng Softw. 2014;69:46–61. doi: 10.1016/j.advengsoft.2013.12.007
  • Muro C, Escobedo R, Spector L, et al. Wolf-pack (Canis lupus) hunting strategies emerge from simple rules in computational simulations. Behav Processes. 2011;88:192–197. doi: 10.1016/j.beproc.2011.09.006
  • Mosav SK, Jalalian E, Gharahchopog FS. A comprehensive survey of grey wolf optimizer algorithm and its application. Int J Adv Robot & Expert Syst (JARES). 2018;1(6):23–45.
  • Faris H, Mirjalili S. Grey wolf optimizer: a review of recent variants and applications. Neural Comput Appl. 2018;30:413–435. doi: 10.1007/s00521-017-3272-5
  • Panda M, Dan B. Grey wolf optimizer and its applications: a survey. In: Proceedings of the Third International Conference on Microelectronics, Computing and Communication Systems. 2019.p. 179–194.
  • Ali S, Sharma A, Jadon S. A survey on grey wolf optimizer. J Emerg Technol Innov Res (JETIR). 2020;7(11):789–790.
  • Almufti SM, Ahmad HB, Marqas RB, et al. Grey wolf optimizer: overview, modifications and applications. Int Res J Sci Technol Educ Manage. 2021;1(1):44–56.
  • Wu G, Mallipeddi R, Suganthan P. Ensemble strategies for population-based optimization algorithms – A survey. Swarm Evol Comput. 2019;44:695–711. doi: 10.1016/j.swevo.2018.08.015
  • Mirjalili S. How effective is the grey wolf optimizer in training multi-layer perceptrons. Appl Intell. 2015;43:150–161. doi: 10.1007/s10489-014-0645-7
  • Muangkote N, Sunat K, Chiewchanwattana S. An improved grey wolf optimizer for training q-Gaussian Radial Basis Functional-link nets, 2014 International Computer Science and Engineering Conference (ICSEC); 2014.
  • Saremi S, Mirjalili SZ, Mirjalili SM. Evolutionary population dynamics and grey wolf optimizer. Neural Comput Appl. 2015;26:1257–1263. doi: 10.1007/s00521-014-1806-7
  • Shankar K, Eswaran P. A secure visual secret share (VSS) creation scheme in visual cryptography using elliptic curve cryptography with optimization technique. Aust J Basic Appl Sci. 2015;9(36):150–163.
  • Jian Z, Zhu G. Affine invariance of meta-heuristic algorithms. Inf Sci (Ny). 2021;576:37–53. doi: 10.1016/j.ins.2021.06.062
  • Niu P, Niu S, Liu N, et al. The defect of the grey wolf optimization algorithm and its verification method. Knowl Based Syst. 2019;171:37–43. doi: 10.1016/j.knosys.2019.01.018
  • Askari Q, Younas I, Saeed M. Emphasizing the importance of shift invariance in metaheuristics by using whale optimization algorithm as a test bed. Soft Comput. 2021;25:14209–14225. doi: 10.1007/s00500-021-06101-9
  • Tatsumi K, Kinoshita N. Shift-invariant grey wolf optimizer exploiting reference points and random selection of step-sizes. Proc SICE Ann Conf. 2022;2022:1201–1206.
  • Kennedy J, Eberhart RC. Particle swarm optimization. Proc IEEE Int Jt Conf Neural Netw. 1995;4:1942–1948.
  • Poli R, Kennedy J, Blackwell T. Particle swarm optimization – an overview. Swarm Intell. 2007;1:33–57. doi: 10.1007/s11721-007-0002-0
  • Yang XS. Nature-Inspired metaheuristic algorithms. Frome: Luniver Press; 2008.
  • Fister I, Fister J.I, Yang XS, et al. A comprehensive review of firefly algorithms. Swarm Evol Comput. 2013;13:34–46. doi: 10.1016/j.swevo.2013.06.001
  • Grey Wolf Optimizer (GWO) version 1.6 (1.85 MB) by Mirjalili S. GWO is a novel meta-heuristic algorithm for global optimization. https://www.mathworks.com/matlabcentral/fileexchange/44974-grey-wolf-optimizer-gwo.
  • Awad NH, Ali MZ, Suganthan PN, et al. Problem definitions and evaluation criteria for the CEC 2017 special session and competition on single objective real-parameter numerical optimization, Technical Report of Nanyang Technological Univ., Jordan Univ. and Zhengzhou Univ., 2016.
  • Clerc M. Particle swarm optimization. London: ISTE Publishing; 2006.
  • Mirjalili S, Lewis A. The whale optimization algorithm. Adv Eng Softw. 2016;95:51–67. doi: 10.1016/j.advengsoft.2016.01.008