Artificial bee colony algorithm with time-varying strategy

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

Research output: Journal PublicationArticlepeer-review

5 Citations (Scopus)
56 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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