Reasonable selection of passenger flow routes consideringdifferent transportation organization modes can meetthe demands of adapting to large-scale high-speed railwaynetworks and improving network efficiency. Passenger flowrouting models are developed to find and optimize a setof passenger flow routes for a high-speed railway network considering different transportation organization modes. In this paper, we presented a new approach minimizing the operating costs, including traveling cost, cost of travel time differences between different lines, and penalties for the inter-line. The network was reconstructed to solve the directed graph with four nodes (node-in-up, node-in-down, nodes-outup, and nodes-out-down) indicating one station. To tackle our problem, we presented an integer non-linear programming model, and direct passenger demand was guaranteed owing to volume constraints. Binary variables were introduced to simplify the model, and the algorithm process was optimized. We suggested a global optimal algorithm by Lingo 11.0. Finally, the model was applied to a sub-network of the Northeast China railway system. Passenger flow routes were optimized and the transportation organization mode was discussed based on passenger volume, traveling distance, and infrastructure.