An improved artificial bee colony algorithm

The Artificial Bee Colony (ABC) algorithm is a new swarm optimization algorithm with good numerical optimization results. This paper presents an improved algorithm called fast mutation artificial bee colony algorithm or FMABC. During choosing food sources, the onlookers use the pheromone and the sen...

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Veröffentlicht in:2011 3rd International Conference on Computer Research and Development Jg. 2; S. 174 - 177
Hauptverfasser: Xiaojun Bi, Yanjiao Wang
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.03.2011
Schlagworte:
artificial bee colony algorithm
Benchmark testing
Classification algorithms
Educational institutions
numerical optimization
opposition-based learning
Optimization
selection sechem
Signal processing algorithms
Stability analysis
Wheels
ISBN:1612848397, 9781612848396
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Beschreibung
Zusammenfassung:The Artificial Bee Colony (ABC) algorithm is a new swarm optimization algorithm with good numerical optimization results. This paper presents an improved algorithm called fast mutation artificial bee colony algorithm or FMABC. During choosing food sources, the onlookers use the pheromone and the sensitivity model in Free Search algorithm to replace the traditional roulette wheel selection model. Then, a mutation strategy based on opposition-based learning was proposed instead of the behavior of scouts. Application of this improved ABC algorithm on seven benchmark optimization functions shows a marked improvement in performance over the traditional ABC.
ISBN:1612848397
9781612848396
DOI:10.1109/ICCRD.2011.5764108