Network　Function　Virtualization　addresses　the　defect　of　traditional　middleboxes　and　enables　operators　to　implement　new　services　through　a　process　named　Service　Function　Chain　mapping.　Service　Function　Chain　is　composed　by　a　sequence　of　Virtual　Network　Functions　(VNFs)　which　is　deployed　in　shared　platforms.　Service　Function　Chain　with　parallel　VNFs　is　proposed　to　reduce　the　delivery　latency.　In　this　paper,　a　multiple　instances　mapping　scheme　named　MIM　is　proposed　to　resolve　the　performance　bottleneck　introduced　by　the　imbalance　of　parallel　VNFs.　A　integer　programing　model　is　established　to　describe　the　multiple　instances　mapping　problem　based　on　queuing　theory,　and　a　double　layer　Genetic　Algorithm　is　used　to　allocate　parallel　VNFs　with　multiple　instances.　Simulation　results　show　that　the　multiple　instances　mapping　scheme　can　improve　the　performance　of　Service　Function　Chain　with　parallel　VNFs　effectively.　©　The　Author(s)　2019.