A comprehensive survey of honey badger optimization algorithm and meta-analysis of its variants and applications

Franklin Open, Год журнала: 2024, Номер 8, С. 100141 - 100141

Опубликована: Авг. 10, 2024

Metaheuristic algorithms are commonly used in solving complex and NP-hard optimization problems various fields. These have become popular because of their ability to explore exploit solutions problem domains. Honey Badger Algorithm (HBA) is a population-based metaheuristic algorithm inspired by the dynamic hunting strategy honey badgers, utilizing digging-seeking techniques. Since its introduction 2020, HBA has garnered widespread attention been applied across This review aims comprehensively survey improvement application problems. Additionally, conducts meta-analysis HBA's improvements, hybridization since introduction. According result survey, 52 studies presented improved using chaotic maps, levy flight mechanism, adaptive mechanisms, transfer functions, multi-objective mechanism opposition based learning techniques, 20 hybrid with other metaheuristics 101 uses original for wide acceptance within research community stems from straightforwardness, ease use, efficient computational time, accelerated convergence speed, high efficacy, capability address different kind issues, distinguishing it well-known approches presented.

Язык: Английский

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Path planning for a UGV using Salp Swarm Algorithm

Опубликована: Апрель 19, 2024

Язык: Английский

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The confluence of PSO and MDO: a bibliometric perspective

Опубликована: Апрель 19, 2024

Язык: Английский

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Optimizing Microarray Gene Selection in Colon Cancer: An Enhanced Metaheuristic Algorithm for Feature Selection

Communications in computer and information science, Год журнала: 2024, Номер unknown, С. 76 - 86

Опубликована: Окт. 16, 2024

Язык: Английский

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