2022
DOI: 10.1016/j.asoc.2022.108634
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Multi-strategy firefly algorithm with selective ensemble for complex engineering optimization problems

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Cited by 37 publications
(13 citation statements)
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“…This is indicated that when considering the correlation in the imputation process, a Firefly Algorithm (FA) was used. However, the use of the FA algorithm which has been developed in other studies for optimization such as [23][24][25][26] can be tried in further research to handle missing data with a class center approach.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…This is indicated that when considering the correlation in the imputation process, a Firefly Algorithm (FA) was used. However, the use of the FA algorithm which has been developed in other studies for optimization such as [23][24][25][26] can be tried in further research to handle missing data with a class center approach.…”
Section: Discussionmentioning
confidence: 99%
“…The firefly algorithm (FA) is a heuristic optimization algorithm inspired by nature that is based on the luminescence and attraction behavior of fireflies [23]. The FA algorithm is used for a number of reasons, including its effectiveness in solving continuous optimal problems [24], it's a simple and effective swarm intelligence algorithm that has garnered significant scholarly attention [25], and its widespread application to the solution of complex engineering optimization problems [26]. However, the FA algorithm's effectiveness in missing data estimation tasks has not been studied [19].…”
Section: Introductionmentioning
confidence: 99%
“…The directed extra random walk formula is defined as: (8) where x i+1 refers to the new position of the firefly after taking a random walk, x i is the current position, α i denotes a random number drawn from uniform distribution U(0, 1), while ub stands for upper bound and lb for the lower bound.…”
Section: Scouting Firefly Algorithmmentioning
confidence: 99%
“…Since its inception almost 15 years ago, FA and its modified variants have demonstrated significant success in various fields of application. For example, in multilevel image segmentation [3], as a way to reduce the number of dimensions [4], optimizing convolutional neural networks [5], solving course timetabling problems [6], and dealing with complex engineering tasks [7], [8], among other things. Knowing that FA has a universal application makes it a fascinating subject to pursue.…”
Section: Introductionmentioning
confidence: 99%
“…Artificial Bee Colony (ABC) [17], Firefly Algorithm (FA) [18][19][20], Cuckoo Search (CS) algorithm [21], etc. Hunger Game Search (HGS) algorithm [22] is a new intelligent optimization algorithm designed according to the hungerdriven activities and behaviors of animals, which have the characteristics of strong merit-seeking ability and fast convergence.…”
Section: Introductionmentioning
confidence: 99%