Swarm intelligence of honey bees had motivated many bio- inspired based optimisation techniques. The Bees Algorithm (BA) was created specifically by mimicking the foraging behavior of foraging bees in searching for food sources. During the searching, the original BA ignores the possibilities of the recruits being lost during the flying. The BA algorithm can become closer to the nature foraging behavior of bees by taking account of this phenomenon. This paper proposes an enhanced BA which adds a neighbourhood search parameter which we called as the Local Search Manoeuvres (LSM) recruitment factor. The parameter controls the possibilities of a bee extends its neighbourhood searching area in certain direction. The aim of LSM recruitment is to decrease the number of searching iteration in solving optimization problems that have high dimensions. The experiment results on several benchmark functions show that the BA with LSM performs better compared to the one with basic recruitment.
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