S1 File - A mixed-integer linear programming method for time-dependent line planning in passenger railway systems by Xin Shi (139139)

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Instances and detailed results of the paper <i>Stochastic scheduling on a restricted batching machine</i> by Yasmin Rios Solis (3909469)

“…We have developed mixed integer programming formulations and solved the stochastic problem using both a Benders decomposition approach and a biased random-key genetic algorithm. …”

MTVRP.ipynb by Brayan Steven Perdomo Cardenas (20553410)

“…This reduces the problem’s dimensionality to routing with multiple trips and a homogeneous fleet. The second phase solves this using mixed-integer linear programming. …”

Variation of the business times of each station. by Xin Shi (139139)

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Distribution of Ave LF for all operated trains. by Xin Shi (139139)

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Variation curves of the CPU time with gap for the 17^th case. by Xin Shi (139139)

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Computational results of the MILP model. by Xin Shi (139139)

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Variation curve of the relevant factors of the input and output data. by Xin Shi (139139)

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Distribution of average waiting time and average load factor. by Xin Shi (139139)

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Extension of a getting-off arc considering time dimension. by Xin Shi (139139)

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The correlation between the Ave time and Ave LF of each train. by Xin Shi (139139)

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Computational results of different passenger service capacities. by Xin Shi (139139)

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Variation curves of the value of the objective function with different passenger service capacities. by Xin Shi (139139)

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Variation curve of the CPU time with different gaps. by Xin Shi (139139)

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Definitions of decision variables. by Xin Shi (139139)

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Auxiliary figure: the correlation between the average waiting time and average load factor of each train. by Xin Shi (139139)

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The directed graph corresponding toFig 1. by Xin Shi (139139)

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A case illustrating the PTC. by Xin Shi (139139)

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Train diagram. by Xin Shi (139139)

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Variation between the and with . by Xin Shi (139139)

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