Facility location of material reserve bases for large railway projects under uncertainty
In order to improve the reliability of the logistics facility network of railway construction projects in complex environments,scenario reduction techniques were used to generate a minimum subset of disruption scenarios and their disruption probabilities to describe the disruption scenarios of transport channels.The polyhedral uncertainty sets were used to describe the uncertainty of logistics demand.To minimize the combined costs of transport,construction,operation and penalty costs,a two-stage stochastic and robust optimisation technique was applied to construct an uncertainty optimisation model for the location of material reserves bases.The model was solved based on a C&CG algorithm.The validity of the model and the algorithm was verified by taking a C railway construction project in a complex environment as an example.The results show that the cost variation coefficient of the model-acquired solutions is 4.3%of the traditional model in the random disruption scenario,and the cost fluctuation of the model-acquired solutions can be up to 38%of that of the traditional model in the extreme demand fluctuation.The two-stage uncertainty optimisation model given in this paper can effectively reduce the cost variation of the logistics facility network resulting from the disruption of transport channels and demand fluctuations.