The　Artificial　Bee　Colony　(ABC)　algorithm　is　a　new　swarm　optimization　algorithm　with　good　numerical　functions　optimization　results.　In　order　to　enhance　the　performance　ability　of　ABC　algorithm,　a　hybrid　ABC　(HAB)　algorithm　is　presented　where　swarming　behavior　of　bacterial　foraging　optimization　algorithm　is　introduced　into　the　ABC　algorithm　to　do　local　search.　The　performance　of　the　proposed　method　is　examined　on　well-known　six　numerical　benchmark　functions　and　the　obtained　results　are　compared　with　basic　ABC　algorithm　and　BFO　algorithm.　The　experimental　results　show　that　the　proposed　approach　is　very　effective　method　for　solving　numeric　benchmark　functions　and　successful　in　terms　of　solution　quality　and　convergence　to　the　global　optimum,　especially　on　the　multimodal　functions.　©　2015　IEEE.