Flight　rescheduling　problems　have　received　considerable　attention　in　recent　decades,　but　most　studies　have　neglected　the　role　of　airline　decision-making　and　passenger　satisfaction,　which　greatly　affects　airline　competitiveness.　In　this　paper,　an　airline-driven　arrival　flight　rescheduling　problem　considering　passenger　satisfaction　is　investigated　when　a　ground　delay　program　(GDP)　is　issued.　An　improved　NSGA-II　(iNSGA-II)　is　tailored　to　solve　the　proposed　bi-objective　model,　aiming　to　minimize　the　total　relevant　cost　and　maximize　passenger　satisfaction,　where　passenger　satisfaction　is　portrayed　using　Prospect　Theory.　As　the　model　considers　multiple　recovery　strategies,　a　chromosome　coding　method　is　designed,　and　population　initialization,　crossover,　and　mutation　are　tailored　to　match　the　problem　characteristics.　Additionally,　the　de-duplication　strategy,　probability　selection,　and　perturbation　strategy　are　introduced　to　enhance　the　algorithm＇s　developmental　capabilities.　The　external　archive　is　also　implemented　to　maintain　population　diversity.　The　optimal　key　parameters　used　in　iNSGA-II　are　obtained　by　the　Taguchi　method.　The　experimental　results　prove　that　the　solution　of　iNSGA-II　outperforms　the　traditional　first-come-first-served　(FCFS)　and　can　find　a　reasonable　solution　set　close　to　the　&　varepsilon;\documentclass[12pt]{minimal}　\usepackage{amsmath}　\usepackage{wasysym}　\usepackage{amsfonts}　\usepackage{amssymb}　\usepackage{amsbsy}　\usepackage{mathrsfs}　\usepackage{upgreek}　\setlength{\oddsidemargin}{-69pt}　\begin{document}$$\epsilon　$$\end{document}-constraint　method　in　less　time.　Meanwhile,　it　is　verified　that　iNSGA-II　has　better　performance　and　is　more　conducive　to　finding　the　global　better　Pareto　fronts　by　comparing　with　NSGA-II,　MOEA/D,　and　MOPSO,　which　can　better　provide　the　basis　for　the　airline＇s　preference　decision.　Finally,　management　insights　are　given　by　analyzing　solutions　and　the　distribution　of　objective　values.　The　research　can　offer　theoretical　insights　and　practical　guidance　to　assist　airlines　in　rescheduling　flights.