This　paper　investigates　a　dynamic　advanced　planning　and　scheduling　(DAPS)　problem　where　new　orders　arrive　on　a　continuous　basis.　A　periodic　policy　with　a　frozen　interval　is　adopted　to　increase　stability　on　the　shop　floor.　A　genetic　algorithm　is　developed　to　find　a　schedule　such　that　both　production　idle　time　and　penalties　on　tardiness　and　earliness　of　both　original　orders　and　new　orders　are　minimized　at　each　rescheduling　point.　The　proposed　methodology　is　tested　on　a　series　of　examples.　A　representative　example　is　illustrated　to　indicate　that　the　suggested　approach　can　improve　the　schedule　stability　while　retaining　efficiency.　©　2006　Elsevier　Ltd.　All　rights　reserved.