Flexible　job　shop　scheduling　is　one　of　the　most　effective　methods　for　solving　multiple　varieties　and　small　batch　production　problems　in　discrete　manufacturing　enterprises.　However,　limitations　of　actual　transportation　conditions　in　the　flexible　job　shop　scheduling　problem　(FJSP)　are　neglected,　which　limits　its　application　in　actual　production.　In　this　paper,　the　constraint　influence　imposed　by　finite　transportation　conditions　in　the　FJSP　is　addressed.　The　coupling　relationship　between　transportation　and　processing　stages　is　analyzed,　and　a　finite　transportation　conditions　model　is　established.　Then,　a　three-layer　encoding　with　redundancy　and　decoding　with　correction　is　designed　to　improve　the　genetic　algorithm　and　solve　the　FJSP　model.　Furthermore,　an　entityJavaScript　Object　Notation　(JSON)　method　is　proposed　for　transmission　between　scheduling　services　and　Digital　Twin　(DT)　virtual　equipment　to　apply　the　scheduling　results　to　the　DT　system.　The　results　confirm　that　the　proposed　finite　transportation　conditions　have　a　significant　impact　on　scheduling　under　different　scales　of　scheduling　problems　and　transportation　times.