This　paper　proposes　a　clustering-based　heuristic,　named　average　Chebyshev　linkage　directed　search　(ACLDS),　to　optimize　the　nozzle　and　feeder　assignments　in　a　single　spin-head　gantry-type　collect-and-place　(CAP)　surface-mount　technology　machine.　The　CAP　machine　is　widely　used　in　the　printed　circuit　board　assembly　(PCBA)　of　consumer　electronic　products,　but　still　a　challenging　application　field　from　an　operations　research　perspective.　The　PCBA　optimization　of　a　single　machine　is　decomposed　into　interrelated　nozzle　assignment,　feeder　assignment,　and　CAP　sequence　subproblems,　which　is　treated　as　a　special　case　of　the　capacitated　location　routing　problem.　Because　of　the　NP-hard　nature　of　this　problem,　the　ACLDS　is　proposed　to　solve　it　efficiently,　which　is　a　hierarchical　heuristic　to　obtain　the　optimal　nozzle　assignment　and　then　optimize　feeder　assignment　and　CAP　sequence　iteratively.　A　clustering　technique　is　applied　in　the　ACLDS　to　group　components　based　on　their　nozzle　and　component　types　in　the　consideration　of　the　optimal　CAP　sequence.　To　investigate　the　efficiency　of　the　proposed　algorithm,　13　industrial　PCB　samples　and　40　artificial　samples　are　used　for　experiments.　Compared　with　the　adaptive　simulated　annealing　algorithm,　the　large　clusters　of　operations　algorithm,　the　hybrid　genetic　algorithm　2　algorithm,　industrial　package,　and　the　adaptive　nearest　neighbor　tabu　search　algorithm,　the　proposed　algorithm　demonstrates　its　efficiency　by　testing　through　both　the　industrial　and　artificial　PCB　samples.　Note　to　Practitioners　-　The　production　efficiency　of　the　collect-and-place　(CAP)　surface-mount　technology　machine　is　critical　to　the　electronic　manufacturing.　This　paper　is　motivated　by　an　optimization　project　cooperated　with　a　spin-head　gantry-type　CAP　machine　manufacturer.　To　minimize　the　CAP　cost,　this　paper　proposed　a　clustering-based　heuristic,　named　average　Chebyshev　linkage　directed　search　(ACLDS),　to　optimize　the　nozzle　assignment,　feeder　assignment,　and　CAP　sequence.　Based　on　the　experimental　results,　the　single-solution-based　ACLDS　outperforms　other　population-based　heuristics,　for　instance,　genetic　algorithm,　in　terms　of　the　solution　quality　and　computational　expense.　Because　the　number　of　nozzle　types　is　typically　no　more　than　five　in　high-speed　machines,　the　enumeration　method　can　be　applied　to　obtain　the　optimal　nozzle　assignment　in　the　ACLDS,　which　has　been　proven　to　be　significant　for　the　printed　circuit　board　assembly　(PCBA)　optimization.　The　proposed　heuristic　can　be　applied　to　both　the　rotary-head　and　revolver-head　gantry-type　CAP　machines.　It　can　be　extended　to　solve　the　optimization　problems　of　dual-gantry　operation　or　line　balance　in　the　PCBA.　This　paper　assumes　the　mass　production　situation　in　the　PCBA,　which　is　not　suitable　for　high-mix　and　low-volume　situations.　©　2004-2012　IEEE.