Abstract
Rail transport system is considered as one of the most sustainable transportation modes with low carbon emissions per kilometer and unit transported. However, investing in rail infrastructure comes with significant construction costs. Therefore, the design of a rail transport system must be carefully planned, taking into account many relevant factors. In this research, we determine the optimal location of transportation hubs in the rail transport network using a multi-objective mathematical model with objectives of minimizing the total cost of transportation and minimizing the maximum passenger travel time in transportation network. The model is tested and applied to a real-world case study in the rail transport system of Thailand. Because the complexity of the multi-objective mathematical model and the large-scale of real case study, we develop a metaheuristics algorithm to efficiently solve this problem. The algorithm is based on the Tabu Search method and is designed to explore non-dominated neighborhoods. This approach allows the model to handle large-scale problems within a reasonable time frame while generating Pareto fronts. The results demonstrate the effectiveness of multi-objective optimization in supporting rail hub location planning.
Published Version
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