An adaptive bacterial foraging optimization algorithm with lifecycle and social learning
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Publication:1925498
DOI10.1155/2012/409478zbMath1253.90224OpenAlexW2111951804WikidataQ58700526 ScholiaQ58700526MaRDI QIDQ1925498
Publication date: 18 December 2012
Published in: Discrete Dynamics in Nature and Society (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1155/2012/409478
Learning and adaptive systems in artificial intelligence (68T05) Approximation methods and heuristics in mathematical programming (90C59)
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A hybrid artificial bee colony optimizer by combining with life-cycle, Powell's search and crossover
Cites Work
- A clustering approach using cooperative artificial bee colony algorithm
- Gradient methods with adaptive step-sizes
- Stability analysis of the reproduction operator in bacterial foraging optimization
- Biomimicry of social foraging bacteria for distributed optimization: Models, principles, and emergent behaviors
- A comparative study of artificial bee colony algorithm
- A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm
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