Fruit　fly　optimization　algorithm　(FOA)　is　a　novel　bio-inspired　technique,　which　has　attracted　a　lot　of　researchers’　attention.　In　order　to　improve　the　performance　of　FOA,　a　modified　FOA　is　proposed　which　adopts　the　phase　angle　vector　to　encoded　the　fruit　fly　location　and　brings　in　the　double　sub-swarms　mechanism.　This　new　strategies　can　enhance　the　search　ability　of　the　fruit　fly　and　helps　find　the　better　solution.　Simulation　experiments　have　been　conducted　on　fifteen　benchmark　functions　and　the　comparisons　with　the　basic　FOA　show　that　θ-DFOA　performs　better　in　terms　of　solution　accuracy　and　convergence　speed.　In　addition,　the　proposed　algorithm　is　used　to　optimization　the　PID　controller,　and　the　promising　performance　is　achieved.　©　Springer　International　Publishing　AG,　part　of　Springer　Nature　2018.