2022
DOI: 10.1016/j.eswa.2021.116450
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Mutation-driven grey wolf optimizer with modified search mechanism

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Cited by 54 publications
(18 citation statements)
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“…Vo and Phan (2013) found a negative relationship between board size and performance for Vietnamese enterprises. The effect of board structure on the profitability of India's software sector was studied by (Singh & Bansal, 2022).…”
Section: Corporate Governance and Firm Financial Performance 251 Boar...mentioning
confidence: 99%
See 1 more Smart Citation
“…Vo and Phan (2013) found a negative relationship between board size and performance for Vietnamese enterprises. The effect of board structure on the profitability of India's software sector was studied by (Singh & Bansal, 2022).…”
Section: Corporate Governance and Firm Financial Performance 251 Boar...mentioning
confidence: 99%
“…Studies on the correlation between audit committee size and company performance have generally come up empty. This includes work by Darko et al (2016), Almoneef and Samontaray (2019); Darko et al (2016); Khalifa H (2018); Rahman and Saima (2018); Singh and Bansal (2022) among others. H6: The ACS and the business's financial success are statistically significant and positively associated.…”
Section: The Audit Committee Sizementioning
confidence: 99%
“…To improve the performance of the GWO, a new variant of the GWO called a mutation-driven modified grey wolf optimizer and denoted by MDM-GWO is proposed. The MDM-GWO combines a new update search mechanism, modified control parameter, mutation-driven scheme, and greedy approach of selection in the search procedure of the GWO [ 46 ]. SCGWO algorithm combines GWO with an improved spread strategy and a chaotic local search mechanism to accelerate the convergence rate of the evolving agents [ 47 ].…”
Section: Related Workmentioning
confidence: 99%
“…The first subcategory of heuristics consists of algorithms inspired by evolution concepts, referred to as Evolutionary Algorithms (EAs) [41], which include Genetic Algorithms (GA) [42,43] and Differential Evolution [44,45]. The other type of algorithms is swarm-based or population-based algorithms, which are inspired by animal behaviors [46], Particle Swarm Optimization (PSO) [47,48], Gray-Wolf Optimization (GWO) [49,50], Cuckoo Search Algorithm [51,52] are just a few examples of swarm intelligence algorithms. In comparison to evolutionary algorithms, swarm intelligence algorithm retains information about search space over iterations, whereas evolutionary algorithms discard the information of previous generations, and swarm intelligence algorithms have few parameters to adjust [53].…”
Section: Algorithm Descriptionmentioning
confidence: 99%