Iterative Configuration of T-Timed Colored Petri Nets by a MILP Model for Rail Freight Volume and Rolling Stock Planning

This study presents a hybrid simulation-optimization framework for the strategic long-term planning of railway operations. The proposed model aims to optimize railway transport planning by ensuring efficient asset allocation, maximizing financial returns, and minimizing asset utilization. It integrates constraints related to operational capacity, such as track and terminal limitations, and market demand, while also assessing the risks of executing planned volumes amid operational uncertainties. By utilizing Mixed Integer Linear Programming (MILP) and T-Timed Colored Petri Net simulations, the model effectively handles the complexities of various cargo types, including grains, fuels, steel products, batch operations, return loads, and mixed trains. Developed in MATLAB, the T-Timed Colored Petri Nets-based simulator enhances the model’s capability to analyze stochastic behaviors and complex correlations. A probabilistic risk assessment (P80) was used to verify the feasibility of the planned volumes. This study provides a detailed guide for implementing this planning tool, demonstrating its adaptability to other planning levels, and suggests potential areas for future enhancements and adaptations.