This　paper　presents　an　optimization　study　of　the　single　gantry　high-speed　rotary-head　collect-and-place　(CAP)　surface　mount　device　(SMD)　machine.　The　rotary-head　gantry-type　CAP　machine　has　the　advantage　of　high　flexibility　and　speed,　which　is　widely　used　in　the　PCB　assembly　of　smart　phones,　tablets,　laptops,　and　monitors.　However,　the　pick-and-place　process　in　SMD　machines　is　the　most　time-consuming　stage　that　determines　the　cycle　time　of　a　PCB　assembly　lines.　This　single　gantry　optimization　problem　can　be　decomposed　into　nozzle　assignment,　feeder　assignment,　and　component　pick-and-place　sequence　problems.　Because　they　are　highly　interrelated　to　each　other,　an　integer　programming　model　is　developed　to　solve　them　simultaneously.　Based　on　the　operational　characteristics　of　high-speed　machines,　an　adaptive　nearest　neighbor　tabu　search　(ANNTS)　is　proposed　to　integrate　the　solution　processes　of　feeder　assignment,　pick-and-place　sequence,　and　multiple　nozzle　types　assignment.　Compared　to　CPLEX　results,　the　ANNTS　finds　all　optimal　solutions　of　14　randomly　generated　small-sized　data　sets.　Another　13　industrial　data　sets　are　used　to　test　the　variants　of　the　ANNTS,　which　include　different　initial　solutions　and　search　heuristics.　Compared　to　the　large　clusters　of　operations　(LCO)　heuristic　(Kulak　et　al.　Int　J　Prod　Res　45(17):　3949-3969,　2007),　the　ANNTS　yields　a　23.32　%　distance　saving　on　average　for　the　single　nozzle　type　problems.　The　ANNTS　improves　the　productivity　by　5.79　%　on　average,　compared　to　the　industrial　package　results.