Generic placeholder image

Recent Advances in Computer Science and Communications

Editor-in-Chief

ISSN (Print): 2666-2558
ISSN (Online): 2666-2566

Review Article

A Comprehensive Survey on Grey Wolf Optimization

Author(s): Isha Sharma, Vijay Kumar* and Sanjeewani Sharma

Volume 15, Issue 3, 2022

Published on: 07 October, 2020

Article ID: e180322186729 Pages: 11

DOI: 10.2174/2666255813999201007165454

Price: $65

Abstract

Grey wolf optimizer is a recently developed metaheuristic algorithm that mimics hunting and social behaviour. It has been applied in most of the engineering design problems. Grey wolf optimizer and its variants have been effectively used to solve real-life applications. For some complex problems, a grey wolf optimizer has been hybridized with other metaheuristics. This paper summarizes the overview of the grey wolf optimizer and its variants. The pros and cons of these variants have been discussed. The application of a grey wolf optimizer has also been discussed with future research directions. This paper will encourage the researchers to use this algorithm for their real-life problems.

Keywords: Grey wolf optimizer, optimisation, metaheuristic, swarm intelligence, social hierarchy, exploration.

Graphical Abstract
[1]
N. Mittal, U. Singh, and B.S. Soni, "Modified grey wolf optimizer for global engineering optimization", Appl. Comput. Intell. Soft Comput., vol. 2016, no. 4598, pp. 1-16, Mar 2016.
[http://dx.doi.org/10.1155/2016/7950348]
[2]
X. Yao, Y. Liu, K. Liang, and G. Lin, "Fast evolutionary computing", In Advances in Evolutionary Computing, 2003, pp. 45-94.
[3]
A.K. Qin, and P.N. Suganthan, "Self-adaptive differential evolution algorithm for numerical optimization", In 2005 IEEE Congress on Evolutionary Computation, vol. 2, pp. 1785-1791, 2005.
[http://dx.doi.org/10.1109/CEC.2005.1554904]
[4]
R. Eberhart, and J. Kennedy, "Particle swarm optimization", In Proceedings IEEE International Conference on Neural Networks, vol. 4, pp. 1942-1948, 1995.
[5]
V. Kumar, "Modified grey wolf algorithm for optimization problems", In: 2016 IEEE International Conference on Inventive Computation Technologies (ICICT), vol. 3. 2016, pp. 1-5.
[http://dx.doi.org/10.1109/INVENTIVE.2016.7830162]
[6]
S. Arora, and H. Joshi, "Enhanced grey wolf optimization algorithm for constrained optimization problems", Int. J. Swarm Intell., vol. 3, no. 2-3, pp. 126-151, Jan 2017.
[7]
W. Gai, C.J. Qu, J. Liu, and J. Zhang, "An improved grey wolf algorithm for global optimization", In 2018 IEEE Chinese Control And Decision Conference (CCDC), 2018, pp. 2494-2498.
[http://dx.doi.org/10.1109/CCDC.2018.8407544]
[8]
Z. Gao, and J. Zhao, "An improved grey wolf optimization algorithm with variable weights", Comput. Intell. Neurosci., vol. 2019, p. 13, June 2019.
[9]
P. Niu, S. Niu, N. Liu, and L. Chang, "Defect of grey wolf optimization algorithm & its verification method", Knowl. Based Syst., vol. 171, pp. 37-43, May 2019.
[http://dx.doi.org/10.1016/j.knosys.2019.01.018]
[10]
H. Yu, Y. Yu, Y. Liu, Y. Wang, and S. Gao, "Chaotic grey wolf optimization", In 2016 IEEE International Conference on Progress in Informatics and Computing (PIC), 2016, pp. 103-113.
[http://dx.doi.org/10.1109/PIC.2016.7949476]
[11]
M. Kohli, and S. Arora, "Chaotic grey wolf optimization algorithm for constrained optimization problems", J. Comput. Des. Eng., vol. 5, no. 4, pp. 458-412, Oct 2018.
[http://dx.doi.org/10.1016/j.jcde.2017.02.005]
[12]
R.A. Ibrahim, M.A. Elaziz, and S. Lu, "Chaotic opposition based grey wolf optimization algorithm based on differential evolution & disruption operator for global optimization", Expert Syst. Appl., vol. 108, pp. 1-27, 2018.
[http://dx.doi.org/10.1016/j.eswa.2018.04.028]
[13]
D. Jai, and I. Kongchuen, "A hybrid differential evolution with grey wolf optimizer for continuous global optimization", In 2015 7th International Conference on Information Technology & Electrical Engineering, 2015, pp. 51-54.
[14]
H. Xu, L. Xiang, and J. Su, "An improved grey wolf optimizer algorithm integrated with Cuckoo search", In 2017 9th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems, vol. 1, pp. 490-493, 2017.
[http://dx.doi.org/10.1109/IDAACS.2017.8095129]
[15]
S.B. Waykar, and C.R. Bharathi, "Adaptive grey wolf optimizer for content-based retrieval of lecture videos", J. Adv. Res. Dyn. Contr. Syst., vol. 11, no. 6, pp. 72-82, 2020.
[16]
N. Singh, and S.B. Singh, "Hybrid algorithm of particle swarm optimization & grey wolf optimization for improving convergence performance", J. Appl. Math., vol. 2017, p. 15, Nov 2017.
[http://dx.doi.org/10.1155/2017/2030489]
[17]
S. Sankarnarayanan, G. Swaminathan, N. Sivakumaran, and T.K. Radhakrishnan, "A novel hybridized grey wolf optimization for a cost optimal design of water distribution network", In 2017 IEEE Computing Conference, 2017, pp. 961-970.
[18]
N. Singh, and H. Hachimi, "A new hybrid whale optimizer algorithm with mean strategy of grey wolf optimizer for global optimization", Math. Computat. Appl., vol. 23, no. 1, p. 14, Mar 2018.
[http://dx.doi.org/10.3390/mca23010014]
[19]
J. Barraza, L. Rodriguez, O. Castillo, P. Melin, and F. Valdez, "A new hybridization approach between the fireworks algorithm & grey wolf optimizer algorithm", J. Optim, vol. 2018, no. 1, pp. 1-18, May 2018.
[http://dx.doi.org/10.1155/2018/6495362]
[20]
X. Zhang, Q. Langkang, J. Cheng, and N. Wang, "A novel hybrid algorithm based on biogeography-based optimization & grey wolf optimizer", Appl. Soft Comput., vol. 67, pp. 197-214, June 2018.
[http://dx.doi.org/10.1016/j.asoc.2018.02.049]
[21]
C. Lu, S. Xiao, X. Li, and L. Gao, "An effective multi-objective discrete grey wolf optimizer for a real-world scheduling problem in welding production", Adv. Eng. Softw., vol. 99, pp. 161-176, Sep 2016.
[http://dx.doi.org/10.1016/j.advengsoft.2016.06.004]
[22]
N.K. Singh, and V. Mahajan, "Detection of cyber cascade failure in smart grid substation using advance grey wolf optimization", J. Interdiscip. Math., vol. 23, no. 1, pp. 69-79, Jan 2020.
[http://dx.doi.org/10.1080/09720502.2020.1721664]
[23]
H.A. Badawy, E. Emary, M. Yassiln, and M. Fathi, "Discrete grey wolf optimization for shredded document reconstruction", In International Conference on Advanced Intelligent System and Informatics, Springer: Cham, 2018, pp. 284-293.
[24]
C.J. Madan, and N. Kumar, "Fuzzy grey wolf optimization for controlled low-voltage ride-through conditions in grid-connected wind turbine with doubly fed induction generator", Simulation, vol. 95, no. 4, pp. 327-338, Apr 2019.
[25]
Z. Li, Y. He, H. Li, Y. Li, and X. Guo, "A novel discrete grey wolf optimization for solving bounded knapsack problem", In International Symposium on Intelligence Computation and Applications, Springer: Singapore, 2018, pp. 101-114.
[26]
H. Komijani, M. Masoumnezhad, M.M. Zanjireh, and M. Mir, "Robust hybrid fractional order proportional derivative sliding mode controller for robot manipulator based on extended grey wolf optimizer", Robotica, vol. 38, no. 4, pp. 605-616, Apr 2020.
[27]
S. Han, "Modified grey-wolf algorithm optimized fractional-order sliding mode control for unknown manipulators with a fractional-order disturbance observer", IEEE Access, vol. 8, pp. 18337-18349, Jan 2020.
[28]
S. Mirjalili, S.M. Mirjalili, and A. Lewis, "Grey wolf optimizer", Adv. Eng. Softw., vol. 69, no. 3, pp. 46-61, Mar 2014.
[http://dx.doi.org/10.1016/j.advengsoft.2013.12.007]
[29]
J. Ji, N. Zhang, C. Liu, and N. Zhong, An ant colony optimization algorithm for learning classification rulesIn 2006 IEEE/WIC/ACM International Conference on Web Intelligence, 2006, pp. 1034-1037.
[http://dx.doi.org/10.1109/WI.2006.35]
[30]
V. Kumar, "Modified grey wolf algorithm for optimization problems", In 2016 IEEE International Conference on Inventive Computation Technologies (ICICT), vol. 3, pp. 1-5, 2016.
[http://dx.doi.org/10.1109/INVENTIVE.2016.7830162]
[31]
W. Lang, and S.J. Xu, "A novel grey wolf optimizer of global optimization problems", In 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, 2016, pp. 1266-1270.
[32]
E. Emary, H.M. Zawbaa, and A.E. Hassanien, "Binary grey wolf optimization approaches for feature selection", Neurocomputing, vol. 172, pp. 371-381, Jan 2016.
[http://dx.doi.org/10.1016/j.neucom.2015.06.083]
[33]
Z. Li, Y. He, H. Li, Y. Li, and X. Guo, "A novel discrete grey wolf optimization for solving bounded knapsack problem", In International Symposium on Intelligence Computation and Applications, Springer: Singapore, 2018, pp. 101-114.
[34]
H. Qin, P. Fan, H. Tang, P. Huang, B. Fang, and B. Pan, "An effective hybrid discrete grey wolf optimizer for casting production scheduling problem with multiobjective & multi constraint", Comput. Ind. Eng., vol. 128, pp. 458-476, Feb 2019.
[http://dx.doi.org/10.1016/j.cie.2018.12.061]
[35]
J. Jayaudhaya, D. Rajasekaran, J. Sumithra, and R. Suresh, "Performance comparison of PV Power processing architecture using boost converter under partial shading condition with grey wolf optimization", J. Crit. Rev., vol. 7, no. 19, pp. 2936-2946, 2020.
[36]
B.H. Abed-alguni, and M. Barhoush, "Distributed grey wolf optimizer for numerical optimization problems", Jordanian J. Comput. Inf. Technol., vol. 4, no. 3, pp. 130-149, Dec 2018.
[37]
S.B. Maind, and P. Wankar, "Artificial neural networks", Int. J. Recent Innov. Trends Comput. Commun., vol. 2, no. 1, pp. 96-100, Jan 2014.
[38]
M. Dorigo, M. Birattari, X. Li, M. Lopez-Ibanez, K. Ohkura, C. Pinciroli, T. Stutzle, Eds., "Swarm Intelligence", 10th International Conference, ANTS 2016, Brussels, Belgium, 2016.
[http://dx.doi.org/10.1007/978-3-319-44427-7]
[39]
J. Srinivas, R. Giri, and S.H. Yang, "Optimization of multi-pass turning using particle swarm intelligence", Int. J. Adv. Manuf. Technol., vol. 40, no. 1-2, pp. 56-66, Jan 2009.
[40]
S. Mirjalili, and A. Lewis, "A whale optimization algorithm", Adv. Eng. Softw., vol. 95, pp. 51-67, May 2016.
[http://dx.doi.org/10.1016/j.advengsoft.2016.01.008]
[41]
E. Emary, H.M. Zawbaa, C. Grosan, and A.E. Hassenian, "Feature subset selection approach by gray-wolf optimization", In Afro-European Conference for Industrial Advancement., Springer: Cham, 2015, pp. 1-13.
[http://dx.doi.org/10.1007/978-3-319-13572-4_1]
[42]
E. Emary, H.M. Zawbaa, and A.E. Hassanien, "Binary grey wolf optimization approaches for feature selection", Neurocomputing, vol. 172, pp. 371-381, Jan 2016.
[http://dx.doi.org/10.1016/j.neucom.2015.06.083]
[43]
E. Emary, W. Yamany, A.E. Hassanien, and V. Snasel, "Multiobjective gray-wolf optimization for attribute reduction", Procedia Comput. Sci., vol. 65, pp. 623-632, Jan 2015.
[http://dx.doi.org/10.1016/j.procs.2015.09.006]
[44]
W. Yamany, E. Emary, and A.E. Hassanien, "New rough set attribute reduction algorithm based on grey wolf optimization", In The 1st International Conference on Advanced Intelligent System and Informatics (AISI2015), 2016, pp. 241-251.
[http://dx.doi.org/10.1007/978-3-319-26690-9_22]
[45]
S.A. Medjahed, S.T. Ait, A. Benyettou, and M. Ouali, "Gray wolf optimizer for hyperspectral band selection", Appl. Soft Comput., vol. 40, pp. 178-186, Mar 2016.
[http://dx.doi.org/10.1016/j.asoc.2015.09.045]
[46]
A.K. Khairuzzaman, and S. Chaudhury, "Multilevel thresholding using grey wolf optimizer for image segmentation", Expert Syst. Appl., vol. 86, pp. 64-76, Nov 2017.
[http://dx.doi.org/10.1016/j.eswa.2017.04.029]
[47]
L. Li, L. Sun, J. Guo, J. Qi, B. Xu, and S. Li, "Modified discrete grey wolf optimizer algorithm for multilevel image thresholding", Comput. Intell. Neurosci., vol. 2017, p. 16, Jan 2017.
[http://dx.doi.org/10.1155/2017/3295769] [PMID: 28127305]
[48]
L. Li, L. Sun, W. Kang, J. Guo, H. Chong, and S. Li, "Fuzzy multilevel image thresholding based on modified discrete grey wolf optimizer and local information aggregation", IEEE Access, vol. 4, pp. 6438-6450, Sep 2016.
[http://dx.doi.org/10.1109/ACCESS.2016.2613940]
[49]
S. Mirjalili, "How effective is the grey wolf optimizer in training multi-layer perceptrons", Appl. Intell., vol. 43, no. 1, pp. 150-161, July 2015.
[http://dx.doi.org/10.1007/s10489-014-0645-7]
[50]
M.R. Mosavi, M. Khishe, and A. Ghamgosar, "Classification of sonar data set using neural network trained by gray wolf optimization", Neural Netw. World, vol. 26, no. 4, p. 393, July 2016.
[http://dx.doi.org/10.14311/NNW.2016.26.023]
[51]
D.K. Geleta, and M.S. Manshahia, "Grey wolf optimizer for optimal sizing of hybrid wind and solar renewable energy system", Comput. Intell., 2020.
[http://dx.doi.org/10.1111/coin.12349]
[52]
V. Kumar, J.K. Chhabra, and D. Kumar, "Grey wolf algorithm based clustering technique", J. Intell. Syst., vol. 26, no. 1, pp. 153-168, 2017.
[http://dx.doi.org/10.1515/jisys-2014-0137]
[53]
S. Zhang, and Y. Zhou, "Grey wolf optimizer based on Powell local optimization method for clustering analysis", Discrete Dyn. Nat. Soc., vol. 2015, p. 17, Nov 2015.
[http://dx.doi.org/10.1155/2015/481360]
[54]
H. Yang, and J. Liu, "A hybrid clustering algorithm based on grey wolf optimizer and k-means algorithm", J. Jiangxi Univ. Sci. Technol., vol. 5, p. 015, 2015.
[55]
Y. Wei, D. Liu, H. Chen, M. Wang, Q. Li, X. Cui, and H. Ye, "An improved grey wolf optimization strategy enhanced SVM and its application in predicting the second major", Math. Probl. Eng., vol. 2017, p. 12, Feb 2017.
[56]
X.Q. Bian, Q. Zhang, L. Zhang, and J. Chen, "A grey wolf optimizer-based support vector machine for the solubility of aromatic compounds in supercritical carbon dioxide", Chem. Eng. Res. Des., vol. 123, pp. 284-294, July 2017.
[57]
Z. Zhou, R. Zhang, Y. Wang, Z. Zhu, and J. Zhang, "Color difference classification based on optimization support vector machine of improved grey wolf algorithm", Optik, vol. 170, pp. 17-29, Oct 2018.
[http://dx.doi.org/10.1016/j.ijleo.2018.05.096]
[58]
E.M. Badr, M.A. Salam, and H. Ahmed, "Optimizing support vector machine using gray wolf optimizer algorithm for breast cancer detection", J. Big Data, 2018.
[59]
S.R. Kamel, R.Y. Zadeh, and M. Kheirabadi, "Improving the performance of support-vector machine by selecting the best features by gray wolf algorithm to increase the accuracy of diagnosis of breast cancer", J. Big Data, vol. 6, no. 1, pp. 1-5, Dec 2019.
[http://dx.doi.org/10.1186/s40537-019-0247-7]
[60]
B. Martin, J. Marot, and S. Bourennane, "Mixed grey wolf optimizer for the joint denoising and unmixing of multispectral images", Appl. Soft Comput., vol. 74, pp. 385-410, Jan 2019.
[61]
A.K. Khairuzzaman, and S. Chaudhury, "Multilevel thresholding using grey wolf optimizer for image segmentation", Expert Syst. Appl., vol. 86, pp. 64-76, Nov 2017.
[62]
P. Padmavathy, S.P. Mohideen, and Gulzar Z, "A novel architecture for a two-pass opinion mining classifier", In International Conference on Advances in Computational Intelligence and Informatics, 2020, pp. 27-35.
[63]
Z. Yue, S. Zhang, and W. Xiao, "A novel hybrid algorithm based on grey wolf optimizer and fireworks algorithm", Sensors, vol. 20, no. 7, p. 2147, Jan 2020.
[http://dx.doi.org/10.3390/s20072147] [PMID: 32290193]
[64]
S. Zhang, and Y. Zhou, "Template matching using grey wolf optimizer with lateral inhibition", Optik, vol. 130, pp. 1229-1243, Feb 2017.
[http://dx.doi.org/10.1016/j.ijleo.2016.11.173]
[65]
C.P. Igiri, Y. Singh, and R.C. Poonia, "A review study of modified swarm intelligence: particle swarm optimization, firefly, bat and gray wolf optimizer algorithms", Recent Adv. Comput. Sci. Commun., vol. 13, no. 1, pp. 48-70, Feb 2020.
[66]
V. Kumar, J.K. Chhabra, and D. Kumar, "Automatic cluster evolution using gravitational search algorithm and its application on image segmentation", Eng. Appl. Artif. Intell., vol. 29, pp. 93-103, Mar 2014.
[http://dx.doi.org/10.1016/j.engappai.2013.11.008]
[67]
D. Agarwal, M.H.W. Qureshi, P. Pincha, P. Srivastava, S. Agarwal, V. Tiwari, and S. Pandey, "GWO‐C: Grey wolf optimizer‐based clustering scheme for WSNs", Int. J. Commun. Syst., vol. 33, no. 8, p. e4344, May 2020.
[68]
V. Kumar, J.K. Chhabra, and D. Kumar, "An astrophysics-inspired grey wolf algorithm for numerical optimization and its application to engineering design problems", Adv. Eng. Softw., vol. 112, pp. 231-254, Oct 2017.
[http://dx.doi.org/10.1016/j.advengsoft.2017.05.008]
[69]
A.C. Pandey, and D.S. Rajpoot, "Feature selection method based on grey wolf optimization and simulated annealing", Recent Adv. Comput. Sci. Commun., vol. 14, no. 2, pp. 635-646, Feb 2021.
[70]
V. Kumar, J.K. Chhabra, and D. Kumar, "Variance-based harmony search algorithm for unimodal and multimodal optimization problems with application to clustering", Cybern. Syst., vol. 45, no. 6, pp. 486-511, Aug 2014.
[http://dx.doi.org/10.1080/01969722.2014.929349]
[71]
V. Kumar, and D. Kumar, "Binary whale optimization algorithm and its application to unit commitment problem", Neural Comput. Appl., vol. 32, pp. 2095-2123, Apr 2020.
[http://dx.doi.org/10.1007/s00521-018-3796-3]
[72]
V. K. Kamboj, "A novel hybrid grey wolf optimizer-simulated annealing algorithm for engineering and power system optimization problems", Recent Adv. Comput. Sci. Commun., 2020.
[73]
V. Kumar, J.K. Chhabra, and D. Kumar, "Automatic unsupervised feature selection using gravitational search algorithm", J. Inst. Electron. Telecommun. Eng., vol. 61, no. 1, pp. 22-31, Jan 2015.
[http://dx.doi.org/10.1080/03772063.2014.987702]
[74]
V. Kumar, J.K. Chhabra, and D. Kumar, "Data clustering using differential search algorithm", J. Sci. Technol., vol. 24, no. 2, pp. 295-306, July 2016.
[75]
R. Kumari, D. Kumar, and V. Kumar, "A conceptual comparison of NSGA-II, OMPSO, and AbYss algorithms", Int. J. Internet Technol. Secur. Trans., vol. 7, no. 4, pp. 330-352, May 2017.
[http://dx.doi.org/10.1504/IJITST.2017.091520]
[76]
S.P. Manikandan, R. Manimegalai, and M. Hariharan, "Gene selection from microarray data using binary grey wolf algorithm for classifying acute leukemia", Curr. Signal Transduct. Ther., vol. 11, no. 2, pp. 76-83, Aug 2016.
[http://dx.doi.org/10.2174/1574362411666160607084415]
[77]
V. Kumar, J.K. Chhabra, and D. Kumar, "Parameter adaptive harmony search algorithm for unimodal and multimodal optimization problems", J. Comput. Sci., vol. 5, no. 2, pp. 144-155, Mar 2014.
[http://dx.doi.org/10.1016/j.jocs.2013.12.001]
[78]
P. Hu, J.S. Pan, and S.C. Chu, "“Improved binary grey wolf optimizer and its application for feature selection”, Knowl.-", Based Syst., vol. 195, p. 105746, May 2020.
[http://dx.doi.org/10.1016/j.knosys.2020.105746]
[79]
D. Kumar, V. Kumar, and R. Kumari, "Automatic clustering using quantum-based multi-objective emperor penguin optimizer and its applications to image segmentation", Modern Phys. Lett. A, vol. 34, no. 24, p. 1950193, Aug 2019.
[http://dx.doi.org/10.1142/S0217732319501931]
[80]
R. Kumari, D. Kumar, and V. Kumar, "Impact of controlling parameters on the performance of MOPSO algorithm", Procedia Comput. Sci., vol. 167, pp. 2132-2139, 2020.
[http://dx.doi.org/10.1016/j.procs.2020.03.261]
[81]
R. Kondabala, V. Kumar, A. Ali, and M. Kaur, "A novel astrophysics-based framework for prediction of binding affinity of glucose binder", Mod. Phys. Lett. B, vol. 34, no. 31, p. 2050346, Nov 2020.
[http://dx.doi.org/10.1142/S0217984920503467]
[82]
V. Kumar, and D. Kumar, "Automatic clustering and feature selection using gravitational search algorithm and its application to microarray data analysis", Neural Comput. Appl., vol. 31, no. 8, pp. 3647-3663, Aug 2019.
[http://dx.doi.org/10.1007/s00521-017-3321-0]
[83]
M. Dehghani, Z. Montazeri, O.P. Malik, G. Dhiman, and V. Kumar, "BOSA: Binary orientation search algorithm", Int. J. Innov. Technol. Explor. Eng., vol. 9, pp. 5306-5310, Nov 2019.
[http://dx.doi.org/10.35940/ijitee.A4215.119119]
[84]
K.K. Kaleka, A. Kaur, and V. Kumar, "Spiral-inspired spotted hyena optimizer and its application to constraint engineering problems", Wirel. Pers. Commun., vol. 116, no. 1, pp. 865-881, Jan 2021.
[85]
A. Kaur, and V. Kumar, "Binary spotted hyena optimizer and its application to feature selection", J. Ambient Intell. Humaniz. Comput., vol. 11, no. 7, pp. 2625-2645, July 2020.
[http://dx.doi.org/10.1007/s12652-019-01324-z]
[86]
K. K. Kaleka, A. Kaur, and V. Kumar, "A conceptual comparison of metaheuristic algorithms and applications to engineering design problems", Int. J. Intell. Inf. Database Syst., vol. 13, no. 2-4, pp. 278-306, Aug 2020.
[87]
J.S. Wang, and S.X. Li, "An improved grey wolf optimizer based on differential evolution and elimination mechanism", Sci. Rep., vol. 9, no. 1, pp. 1-21, May 2019.
[http://dx.doi.org/10.1038/s41598-019-43546-3] [PMID: 31073211]
[88]
Q. Al-Tashi, A. J. Abdulkadir, H. M. Rais, S. Mirjalili, H. Alhussian, M. G. Ragab, and A. Alqushaibi, "Binary multi-objective grey wolf optimizer for feature selection in classification", IEEE Access, vol. 8, pp. 106247-106263, June 2020.
[http://dx.doi.org/10.26782/jmcms.2020.04.00007]
[89]
S. Yadav, S.K. Nagar, and A. Mishra, "Tuning of parameters of PID controller using grey wolf optimizer", In Proceedings of the International Conference on Advances in Electronics, Electrical & Computational Intelligence, 2019, p. 13.

Rights & Permissions Print Cite
© 2024 Bentham Science Publishers | Privacy Policy