To　solve　the　multi-objective　optimization　problem　of　surface　mounting,　a　multi-objective　optimization　model　was　established　with　feeders,　placing　sequence　and　changing　times　of　the　nozzles　as　sub-objectives.　The　concept　of　information　entropy　was　introduced　into　the　grey　correlation　analysis,　and　the　grey　entropy　correlation　analysis　method　was　proposed.　The　original　grey　correlation　degree　was　changed　into　grey　entropy　correlation　degree.　Based　on　grey　entropy　correlation　analysis　method,　the　grey　entropy　correlation　degree　functions　of　three　sub-objectives　were　established　and　a　multi-objective　differential　evolution　algorithm　with　grey　entropy　correlation　was　presented.　The　coding　method　of　real　vector-location　sequence　was　adopted　to　realize　the　application　of　differential　evolution　algorithm　on　surface　mounting　optimization.　The　experimental　results　indicated　that　at　least　two　sub-objectives　in　Pareto　optimal　solutions　of　differential　evolution　algorithm　were　better　than　genetic　algorithm,　and　the　solution　had　better　uniform　distribution.　Therefore,　the　multi-objective　differential　evolution　algorithm　with　grey　entropy　correlation　could　solve　the　multi-objective　optimization　problem　of　surface　mounting　effectively.