Heavy-haul　railway　transport　is　a　critical　mode　of　regional　bulk　cargo　transport.　It　dramatically　improves　the　freight　transport　capacity　of　railway　lines　by　combining　several　unit　trains　into　one　combined　train.　In　order　to　improve　the　efficiency　of　the　heavy-haul　transport　system　and　reduce　the　transportation　cost,　a　critical　problem　involves　arranging　the　combination　scheme　in　the　combination　station　(CBS)　and　scheduling　the　train　timetable　along　the　trains＇　journey.　With　this　consideration,　this　paper　establishes　two　integer　programming　models　in　stages　involving　the　train　service　plan　problem　(TSPP)　model　and　train　timetabling　problem　(TTP)　model.　The　TSPP　model　aims　to　obtain　a　train　service　plan　according　to　the　freight　demands　by　minimizing　the　operation　cost.　Based　on　the　train　service　plan,　the　TTP　model　is　to　simultaneously　schedule　the　combination　scheme　and　train　timetable,　considering　the　utilization　optimal　for　the　CBS.　Then,　an　effective　hybrid　genetic　algorithm　(HGA)　is　designed　to　solve　the　model　and　obtain　the　combination　scheme　and　train　timetable.　Finally,　some　experiments　are　implemented　to　illustrate　the　feasibility　of　the　proposed　approaches　and　demonstrate　the　effectiveness　of　the　HGA.