As　an　important　component　of　data　envelopment　analysis　(DEA),　the　inverse　DEA　method　often　has　no　feasible　solution　under　variable　returns　to　scale　(VRS).　By　analyzing　the　reason　of　this　problem,　the　limitation　of　inputs　and　outputs　in　the　inverse　DEA　method　under　VRS　is　identified.　Then　the　outputs　possible　set　and　the　inputs　possible　set　are　defined　for　different　inverse　DEA　models;　and　some　models　are　thus　developed　to　determine　the　change　range　of　outputs/inputs.　Sequentially,　by　determining　the　optimal　given　outputs/inputs,　the　inverse　DEA　model　under　VRS　is　used　to　estimate　the　optimal　inputs　increment　or　outputs　diminution　for　the　optimal　given　efficiency,　and　the　problem　that　the　inverse　DEA　method　has　no　feasible　solution　is　avoided.　In　addition,　the　effects　of　efficiency　change　and　technological　change　on　the　optimization　of　inputs　and　outputs　are　further　discussed　in　this　paper.　Finally,　two　examples　are　provided　to　illustrate　the　validity　and　effectiveness　of　our　methods.　©　2021　Elsevier　Ltd