An　all-day　bus　schedule　optimization　method　was　proposed　in　consideration　of　passengers＇　demand　between　the　bus　and　the　metro.　Firstly,with　the　goal　of　minimizing　the　cost　of　passenger　waiting　time　and　the　operating　costs　of　public　transportation　enterprises,an　optimization　model　was　constructed.　Then,a　genetic-simulated　annealing　hybrid　algorithm　was　designed　to　solve　the　model.　A　case　study　of　the　upward　direction　of　the　No.　1　bus　in　Fuzhou　was　selected　to　verify　the　effectiveness　and　practicability　of　the　proposed　model　and　algorithm.　After　optimizing　the　schedule,the　average　waiting　time　cost　of　passengers　in　B-M　mode,M-B　mode,and　non-transfer　mode　has　been　reduced　by　19.30%.　Public　transportation　enterprises＇　operating　costs　have　increased　by　4.95%　due　to　increased　bus　departures,but　the　total　system　cost　has　decreased　by　5.05%.　©　2025　Editorial　Board　of　Jilin　University.　All　rights　reserved.