The　excessive　travel　demand　in　the　metro　system　during　peak　hours　may　cause　platform　congestion　and　reduce　the　comfort　of　the　passengers.　Thus,　this　article　proposes　an　approach　for　integrally　optimizing　the　train　timetable　and　passenger　control　on　an　oversaturated　metro　line,　to　improve　the　comfort　of　passengers　on　the　platform.　Specifically,　taking　the　short-term　impact　of　the　boarding/alighting　passengers　into　account,　a　novel　quantitative　assessment　method　of　the　perceived　waiting　time,　considering　the　impact　of　the　platform　passengers＇　density　and　passenger　control　strategy,　named　the　generalized　waiting　time,　is　proposed.　A　mixed-integer　nonlinear　programming　model　is　formulated　to　minimize　the　generalized　waiting　time,　and　a　heuristic　algorithm　based　on　the　adaptive　simulated　annealing　genetic　algorithm　and　the　adaptive　large　neighbourhood　search　(ASAGA-ALNS)　is　designed　to　find　high-quality　solutions.　The　results　of　numerical　experiments　show　that　the　method　can　alleviate　platform　congestion,　while　improving　the　comfort　of　waiting　passengers.