Artificial bee colony algorithm with time-varying strategy

Quande Qin, Shi Cheng, Qingyu Zhang, Li Li, Yuhui Shi

Research output: Journal PublicationArticlepeer-review

6 Citations (Scopus)
8 Downloads (Pure)


Artificial bee colony (ABC) is one of the newest additions to the class of swarm intelligence. ABC algorithm has been shown to be competitive with some other population-based algorithms. However, there is still an insufficiency that ABC is good at exploration but poor at exploitation. To make a proper balance between these two conflictive factors, this paper proposed a novel ABC variant with a time-varying strategy where the ratio between the number of employed bees and the number of onlooker bees varies with time. The linear and nonlinear time-varying strategies can be incorporated into the basic ABC algorithm, yielding ABC-LTVS and ABC-NTVS algorithms, respectively. The effects of the added parameters in the two new ABC algorithms are also studied through solving some representative benchmark functions. The proposed ABC algorithm is a simple and easy modification to the structure of the basic ABC algorithm. Moreover, the proposed approach is general and can be incorporated in other ABC variants. A set of 21 benchmark functions in 30 and 50 dimensions are utilized in the experimental studies. The experimental results show the effectiveness of the proposed time-varying strategy.
Original languageEnglish
Pages (from-to)1-17
JournalDiscrete Dynamics in Nature and Society
Publication statusPublished - 17 Mar 2015


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