Considering　the　dynamic　characteristics　of　manufacturing　unit　needs,　the　line-limiting　policy　of　large　trucks　and　the　exact　constraint　of　delivery　time,　a　two-echelon　vehicle　routing　optimization　method　with　time　window　considering　dynamic　degree　was　designed.　Based　on　the　customer　dynamic　incremental　probability　threshold　and　dynamic　degree,　an　optimized　routing　update　strategy　in　response　to　incremental　demand　was　constructed.　The　continuous　dual　network　optimization　was　innovatively　mapped　to　the　Vehicle　Routing　Problem　with　Time　Windows　(VRPTW)　optimization　of　two　sub-networks,　including　from　the　suburban　delivery　centre　to　the　city　delivery　centre　and　from　the　city　delivery　centre　to　the　customer.　The　four　neighborhood　search　strategies　of　Or-opt,2-opt,2-opt*　and　Swap/shift　were　merged　to　improve　the　parallel　simulated　annealing　algorithm.　Company　case　was　used　to　verify　the　model　and　method,　and　the　results　show　that　the　proposed　method　could　better　meet　the　agility　response　of　suppliers　to　the　dynamic　needs　of　customers,　and　had　good　robustness.　©　2022　CIMS.　All　rights　reserved.