Abstract
Swarm Agents are known for their cooperative and collective behavior and operate in decentralized manner which is regarded as Swarm Intelligence. Various techniques like Ant Optimization, Wasp, Bacterial Foraging, PSO, etc., are proposed and implemented in various real-time applications to provide solutions to various real-time problems especially in optimization. The aim of this paper to present ABC algorithm in a comprehensive manner. The ABC-based SI technique proposed has demonstrated that it has superior edge in solving all types of unconstrained optimization problems. Many researchers have fine-tuned the basic algorithm and proposed different ABC based algorithms. The result show that still lots of work is required mathematically and live implementation in order to enable ABC algorithm to be applied to constrained problems for effective solutions.
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Nayyar, A., Puri, V., Suseendran, G. (2019). Artificial Bee Colony Optimization—Population-Based Meta-Heuristic Swarm Intelligence Technique. In: Balas, V., Sharma, N., Chakrabarti, A. (eds) Data Management, Analytics and Innovation. Advances in Intelligent Systems and Computing, vol 839. Springer, Singapore. https://doi.org/10.1007/978-981-13-1274-8_38
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DOI: https://doi.org/10.1007/978-981-13-1274-8_38
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