Evolutionary　progr　amming　is　a　good　global　optimization　method.　By　introduction　the　improved　adaptive　mutation　operation　and　improved　selection,　the　new　adaptive　evolutionary　programming　is　proposed　in　this　paper.　This　algorithm　is　verified　by　simulation　experiment　of　typical　optimization　function.　Comprehensive　comparisons　with　other　approach　show　that　the　proposed　approach　is　superior　over　other　in　terms　of　learning　efficiency　and　performance.　The　results　of　experiment　show　that,　the　proposed　fast　evolutionary　programming　can　improve　not　only　the　convergent　speed　of　original　algorithm　but　also　the　computation　effect　of　original　algorithm,　and　is　a　very　good　optimization　method.　©　2010　IEEE.