A Multiobjective Optimization for Train Routing at the High-Speed Railway Station Based on Tabu Search Algorithm

Table 3

The scheme of determining initial solution.

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Step 1. Input initial information, including trains’ character, railway station parameters, train speed profiles, trains with transfer relationship, planned timetable, etc., set .

Step 2. Choose a feasible routes set as incumbent solution through prior knowledge of trains and parameters of the railway station, get objective value .

Step 3. Generate neighborhood of , and corresponding neighborhood solution: .

Step 4. Search the best solution in and corresponding routing set

Step 5. If the objective value of is better than that of , , ; otherwise, let as current solution continuously.

Step 6. If the value of does not change, ; otherwise, go to step 7.

Step 7. If , output and the corresponding routing set , stop. Else, go to step 3.

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