It　is　sometimes　necessary　that　offering　an　approximate　model　to　substitute　the　real　complex　problem　in　optimization　solution,　but　which　can　only　approximate　the　original　problem　at　a　certain　extent.　The　optimization　model　on　unreliable　approximation　function　will　lead　to　oscillations　of　the　iterative　objective　functions,　and　make　convergence　of　the　iterations　being　slowly　even　impossibly.　Finally,　the　results　may　not　sometimes　satisfy　the　constraint　conditions.　The　approximate　model　will　increase　the　reliability　in　certain　domain　when　the　move　limits　are　imposed　on　design　variables.　The　strategies　of　giving　move　limits　belong　to　criterion　method　and　they　are　usually　rough,　because　they　are　not　rational　results　according　to　properties　of　constraint　functions.　This　paper　constructs　a　second-order　approximate　explicit　function　by　accumulated　information　which　substitutes　the　accurate　function　of　the　constraint　condition　as　evaluation　function　to　construct　rational　estimation　formula　of　the　move　limits.　Eventually,　rational　move　limits　are　obtained　and　applied　to　SQP　(Sequential　Quadratic　Programming).　Examples　show　it　is　feasible　and　efficient.