There　is　a　lot　of　research　in　genetic　algorithm　about　structural　optimization.　But　as　far　as　the　large　multi-goal　program　concerned　it　here　limited　the　application　of　genetic　algorithm　for　the　reason　of　its　specialty　and　large　calculation.　In　order　to　explore　new　resolution,　the　author　proposed　a　combining　algorithm　for　structural　optimization,　which　is　based　on　genetic　algorithm　and　gradient　algorithm:　Use　gradient　algorithm　to　superpose,　get　a　result,　improve　the　herd　of　genetic　algorithm　with　this　result,　then　compare　the　superior　one　of　genetic　algorithm　with　the　root　of　gradient　algorithm,　choose　the　best　point　to　be　the　incipient　point　of　the　next　step　of　super　position.　With　this　method,　it　can　keep　the　best　root　of　all　the　course,　and　also　it　can　speed　up　searching,　and　keep　the　best　global　root.　Numerical　examples　show　that　the　combining　algorithm　possesses　both　the　merit　of　genetic　algorithm　on　strong　global　searching　ability　and　gradient　algorithm.