Big　cities＇　bi-directional　metro　lines　often　have　unbalanced　passenger　demand,　i.e.,　up-directional　passenger　demand　is　oversaturated　but　down-directional　passenger　demand　is　unsaturated.　In　recent　years,　the　method　to　relieve　congestion　in　oversaturated　direction　has　attracted　much　attention,　but　many　problems　in　the　unsatu-rated　direction　have　not　gotten　as　much　attention,　e.g.,　the　waste　of　transportation　resources　caused　by　low　loading　rate,　and　the　insufficient　utilization　of　platform　space　resources　caused　by　less　waiting　passengers.　To　address　these　problems,　this　paper　introduces　a　new　collaborative　optimization　model　for　the　train　timetable,　passenger　control　and　rolling　stock　schedule　on　a　bi-directional　metro　line　with　unbalanced　passenger　demand.　With　consider　the　real-time　state　of　bi-directional　platform　passengers,　a　platform　passenger　control　strategy　is　designed　to　promote　the　utilization　of　platform　resources,　and　an　empty　train　return　strategy　is　proposed　to　transfer　transportation　resources　to　oversaturated　direction.　To　characterize　the　problem　mathematically,　a　multi-objective　mixed-integer　nonlinear　programming　model　(MINLP)　is　formulated　to　minimize　the　passengers＇　waiting　time,　the　difference　of　bi-directional　platform　passenger　density　and　the　use　cost　of　trains.　An　effective　heuristic　algorithm　based　on　the　non-dominated　sorting　genetic　algorithm　(NSGA-II)　and　the　adaptive　large　neighborhood　search　(ALNS)　is　designed　to　find　high-quality　solutions　for　the　proposed　model.　Finally,　five　sets　of　numerical　examples　based　on　the　Beijing　metro　Batong　line,　are　conducted　to　validate　the　performance　of　the　proposed　method　in　this　paper.　The　experimental　results　demonstrate　the　method　can　fully　utilize　the　trans-portation　and　platform　resources　of　the　unsaturated　direction,　to　improve　transport　efficiency　and　relieve　platform　congestion　of　oversaturated　direction.