Keywords: cooperative behaviours, cooperative bee swarm optimization, numerical functions, colonization, flying patterns
Received December 10, 2009; revised July 21, 2010; accepted August 20, 2010.
Communicated by Tsan-sheng Hsu.
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REZA AKBARI AND KOORUSH ZIARATI
Department of Computer Science and Engineering
Shiraz University
Shiraz, 7134-51154 Iran
A novel Cooperative Bee Swarm Optimization (CBSO) algorithm based on foraging
behaviour of honey bees is presented. The CBSO employs cooperative behaviours of
multiple swarms in optimizing numerical functions. The proposed approach provides
different patterns which are used by the bees to adjust their flying trajectories. The flying
patterns provide an efficient way to balance exploration and exploitation. Cooperation is
obtained by sharing information between swarms through a leader swarm. Also, a colonization
process is performed between swarms. In colonization process a portion of an
extinct swarm is replaced with the individuals from a colonist swarm. The proposed algorithm
was tested on a set of well-known test functions. Results have shown that the
proposed algorithm is efficient, robust, and outperforms other genetic, particle swarm,
and bee algorithms examined in this paper.
Received December 10, 2009; revised July 21, 2010; accepted August 20, 2010.
Communicated by Tsan-sheng Hsu.