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Honey Badger Algorithm/Evidence
Method evidence record

Honey Badger Algorithm

The Honey Badger Algorithm (HBA) is a nature-inspired metaheuristic optimization algorithm presented by Hashim et al. in 2023, modeled on the hunting behavior and intelligent strategies of honey badgers (Mellivora capensis). Honey badgers are known for their remarkable problem-solving abilities, fearlessness, and persistent pursuit of prey and food sources despite significant obstacles. HBA captures these behavioral traits to create an effective optimization framework.

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Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Honey Badger Algorithm
Taxonomic method record · ml-model / optimization
  • Hashim, F. A., Hussain, K., & Houssein, E. H. (2023). Honey badger algorithm: A new meta-heuristic optimization algorithm. Neural Computing and Applications, 35(17), 12265-12287. · URL
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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Taxonomic bucketAquila Optimizermachine-suggested · Relational suggestion, not evidence.Used in the same domainGrey Wolf Optimizermachine-suggested · Relational suggestion, not evidence.Taxonomic bucketHarris Hawks Optimizationmachine-suggested · Relational suggestion, not evidence.Used in the same domainParticle Swarm Optimizationmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketSlime Mould Algorithmmachine-suggested · Relational suggestion, not evidence.

Evidence status

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Sources

1 recorded citation, copied from the method source record.

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