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Harris Hawks Optimization/Evidence
Method evidence record

Harris Hawks Optimization

Harris Hawks Optimization (HHO) is a metaheuristic algorithm introduced by Heidari et al. in 2019, inspired by the hunting strategies of Harris's hawks. The algorithm models the cooperative hunting behavior and escape strategies of these raptors to solve complex optimization problems. HHO balances exploration through perching and exploitation through dynamic pursuit, making it effective for multimodal and high-dimensional optimization.

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Harris Hawks Optimization
Taxonomic method record · ml-model / optimization
  • Heidari, A. A., Mirjalili, S., Faris, H., Aljarah, I., Mafarja, M., & Chen, H. (2019). Harris hawks optimization: Algorithm and applications. Future Generation Computer Systems, 97, 849-872. · DOI 10.1016/j.future.2019.02.028
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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.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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