A novel artificial bee colony algorithm with an adaptive population size for numerical function optimization
DOI10.1016/j.ins.2017.05.044zbMath1435.90153OpenAlexW2617395951WikidataQ113295121 ScholiaQ113295121MaRDI QIDQ778396
Jianyong Chen, Zexuan Zhu, Qiuzhen Lin, Nan Lu, Genghui Li, Laizhong Cui, Ka-Chun Wong, Zhen-Kun Wen
Publication date: 2 July 2020
Published in: Information Sciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.ins.2017.05.044
probability modelartificial bee colony algorithmexploration and exploitationsolution search equationadaptive method for the population size
Evolutionary algorithms, genetic algorithms (computational aspects) (68W50) Stochastic programming (90C15) Approximation methods and heuristics in mathematical programming (90C59)
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Cites Work
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- Adaptive differential evolution algorithm with novel mutation strategies in multiple sub-populations
- A particle swarm inspired multi-elitist artificial bee colony algorithm for real-parameter optimization
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- A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm
- A modified artificial bee colony algorithm based on converge-onlookers approach for global optimization
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