# Research on Railway Emergency Resources Scheduling Model under Multiple Uncertainties
## 1 Introduction
### Literature Review
comprehensively considered the uncertainty of material demands and transportation times on the basis of traditional model analysis and constructed a dual-objective highway emergency resource point location determination model and robust optimization model with the smallest cost and time [23]. [PERSON] et al. introduced interval numbers to describe the uncertainty of material demands and material transportation times on the basis of traditional linear programming and established a multi-objective linear interval programming model, taking the economy, timeliness, and fairness of emergency material distribution as the targets [24]. Although more and more scholars have focused on the practical problems under dual uncertainty and modeling studies, there remains considerable scope for research on the multiple uncertainties as compared to dual uncertainties. Moreover, the existing research primarily focuses on the dispatch of water and electricity resources, while relatively few studies have been conducted in the specific field of railway emergency rescue. This is mainly attributed to the unique characteristics of railway rescue, which include complex rescue scenarios, singular rescue routes, high rescue costs, and time constraints for effective rescue operations. [PERSON] [23] and [PERSON] [24] considered the uncertainty of the demand and transportation times of road emergency rescue supplies in their study but ignored the uncertainty of the limited amount of emergency resource reserves. Although [PERSON]'s study [21] considered the uncertainty of transportation network connectivity and travel times during large-scale emergencies, it ignored the limitations of resource reserves and the critical role they played in rail emergency relief for large-scale disasters, considering only road relief. Railway emergency resources mainly use rescue trains to organize emergency materials, and most of their emergency resources are specialized materials, which may have limited emergency resources when large-scale emergencies occur. Therefore, it is important to explore the optimization of railway emergency resource dispatching under multiple uncertainties. In fact, there are many uncertainties in the process of railway emergency resource management for large-scale emergencies, and they generally manifest in different forms of different parameters, compound uncertainties of the same parameters or the existence of interactions between parameters, which eventually lead to an exceptionally complex system, introducing difficulties to emergency rescue and resource scheduling. The existing uncertainty of planning research focuses mainly on the optimization of emergency resource scheduling with a single uncertainty model, which considers only a single random, fuzzy, or interval. It is difficult to portray complex multiple uncertainty problems accurately, and the optimization results are prone to bias and even lead to poor decisions. Therefore, identifying the multiple uncertainties and complexities of the railway emergency resource management system, revealing the effects of its intrinsic components and their interactions on the railway emergency resource scheduling, constructing the corresponding optimal scheduling model, and providing the decision makers with the optimal decision solution are urgent tasks.