An improved artificial bee colony algorithm
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Yanfei Jia, Xin Wang and Xiaodong Yang
To improve the performance of artificial bee colony algorithm, a modified artificial bee colony algorithm is proposed. The modified ABC algorithm takes advantage of chaotic mapping to enhance diversity in the bee population, uses information of a better solution to guide the search of candidate solutions toward a promising direction that improves exploitation, and introduces a global solution into the scout stage in order to jump out of the local optimal value. The modified ABC
algorithm balances exploration and exploitation, which contradict each other, so that it can achieve optimal performance. Simulation results show the proposed method has more accuracy than the other methods.
Artificial bee colony algorithm, Chaotic mapping, Local optimal value, Exploration.