The　continued　air　traffic　growth　leads　to　more　fuel　consumption　for　the　total　aviation　operation.　Studying　how　to　achieve　energy-saving　operations　through　a　more　reasonable　strategy　under　the　existing　technology　is　still　significant.　This　study　first　constructs　a　two-stage　global　operational　energy　optimization　model　with　stand　assignment　and　GSE　routing　problems,　then　distinguishes　the　scheduling　of　ground　vehicles　based　on　task　attributes　through　a　mathematical　approach　and　also　improves　the　initialization　and　cross-variance　approach　of　the　NSGA-II　algorithm　to　reduce　the　number　of　infeasible　solutions　and　improve　the　solution　speed.　A　case　study　is　carried　out　with　the　operational　data　of　a　Chinese　airport,　and　the　results　show　that　the　strategy　can　help　achieve　about　a　5%　of　reduction　in　operational　fuel　consumption.　This　study　can　provide　theoretical　support　and　a　technical　basis　for　airport　management　to　formulate　relevant　strategies.　©　2023　Elsevier　Ltd