Method evidence record

Artificial Bee Colony

Artificial Bee Colony (ABC) is a population-based swarm intelligence metaheuristic introduced by Karaboga and Basturk in 2007. It models the cooperative foraging behavior of a honey bee colony to search for optimal solutions in continuous numerical optimization problems. The algorithm divides candidate solutions among three bee types — employed, onlooker, and scout — and iteratively refines them through local search and probabilistic selection, making it well-suited for researchers and engineers tackling complex, multimodal optimization landscapes.

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Artificial Bee Colony (ABC) Optimization

Taxonomic method record · process-pipeline / optimization

Karaboga, D., & Basturk, B. (2007). A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm. Journal of Global Optimization, 39(3), 459–471. · DOI 10.1007/s10898-007-9149-x

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Related methods

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Same method familyAnt Colony Optimizationmachine-suggested · Relational suggestion, not evidence.Same method familyGenetic Algorithmmachine-suggested · Relational suggestion, not evidence.Same method familyParticle Swarm Optimizationmachine-suggested · Relational suggestion, not evidence.