To　solve　the　problem　of　airline　flight　disruption　caused　by　emergencies,　this　paper　recovers　the　disrupted　departure　flight.　A　bi-objective　optimization　model　for　minimizing　airline　delay　cost　and　passenger　delay　time　is　constructed.　An　adaptive　non-dominated　sorting　genetic　algorithm-Ⅱ　based　on　dominant　strengths　(ANSGA2-DS)　is　designed.　The　novel　crowding　distance,　the　adaptive　elitist　retention　technique,　and　the　quick　dominant　sorting　approach　are　the　three　enhanced　operations　that　are　given.　The　proposed　algorithm　is　verified　by　the　operation　data　of　an　airline　in　Fuzhou　Changle　International　Airport.　The　experimental　results　reveal　that,　compared　with　the　traditional　first　scheduling　first　serve　method,　the　algorithm　proposed　in　this　paper　can　reduce　the　costs　greatly.　In　contrast　to　the　Ε-constraint　approach,　the　Ε-constrained　approach　requires　a　longer　solution　time,　and　the　resulting　solution　results　are　similar　to　those　of　the　Ε-constrained　approach.　Compared　with　the　NSAG2　algorithm　and　the　MOEAD　algorithm,　the　algorithm　proposed　in　this　paper　shows　better　performance.　The　proposed　algorithm　can　solve　the　problem　effectively　and　efficiently,　and　provide　a　basis　for　airlines　to　reach　an　optimized　solution.　©　2024　Beijing　University　of　Aeronautics　and　Astronautics　(BUAA).　All　rights　reserved.