This　paper　presents　an　adaptive　hybrid　genetic　algorithm　(AHGA)　for　VLSI　standard　cell　placement　problem　which　belongs　to　NP-hard　combinatorial　optimization　problem.　Based　on　the　distinguishing　feature　of　solution　space　of　the　problems　with　various　scale　and　array　or　non-array　placement　style,　we　correspondingly　use　some　adaptive　strategies　to　greatly　reduce　the　runtime.　We　make　innovations　in　the　adaptive　strategies　for　constructing　single　crossover　meme　and　accepting　placement　candidate.　The　experimental　tests　are　performed　on　Peko　suite3　and　ISPD04　benchmark　circuits,　the　results　and　comparisons　show　that　these　strategies　are　efficient.