This　paper　proposes　an　optimization　model　for　electric　bus　scheduling　and　charging　scheduling　with　the　consideration　of　time-of-use　electricity　pricing　policy　and　multiple　vehicle　types,　aiming　to　minimize　the　total　operation　cost　of　electric　bus　system.　The　practical　operational　constraints　of　bus　schedule　chain　formulation,　charging　time　window,　and　limited　number　of　chargers　are　considered　in　the　model.　An　adaptive　large　neighborhood　search　(ALNS)　algorithm　is　proposed　to　solve　the　bus　schedule　optimization　problem.　This　algorithm　incorporates　diverse　destruction　and　repair　operators　tailored　to　the　characteristics　of　the　problem,　such　as　the　trip-to-vehicle　allocation　and　the　feasibility　of　the　bus　schedule　chain　under　multiple　vehicle　types.　For　the　feasible　bus　schedule　chain　combinations　generated　by　ALNS,　the　charging　schedule　optimization　subproblem　under　time-of-use　electricity　price　is　constructed　and　mapped　into　a　dedicated　network.　An　algorithm　based　on　the　minimum-cost-flow　is　designed　to　solve　for　the　charging　duration,　which　leads　to　an　optimal　decision　on　charging　start　time.　The　model　and　algorithm　are　validated　using　three　bus　routes　in　Beijing.　The　results　show　that　compared　with　the　current　situation,　the　fleet　size　is　reduced　from　30　to　24　vehicles,　resulting　in　a　decrease　in　electricity　cost　and　total　operation　cost　by　25.84%　and　20.63%,　respectively.　Comparative　experiments　are　conducted　to　explore　the　impact　of　different　weights　of　repair　indicators　and　combinations　of　vehicle　types　on　the　optimization　results.　©　2024　Science　Press.　All　rights　reserved.