[PERSON] [24] et al. proposed a multi-objective resource allocation model considering the uncertainty and persistence in the rescue process. The results show that MOCGA can better solve the multi-objective dynamic emergency resource allocation model. [PERSON] [25] et al. considered the unpredictability of different emergency scenarios in the subway system, applied the scenario-response model in the resource allocation decision, established a multi-objective model of emergency resource allocation in the subway emergency rescue process, and used a particle swarm optimization algorithm to solve the model, which enhanced the subway emergency rescue capability in practice. [PERSON] [26] et al. studied the optimization model of railway emergency resource scheduling considering the fuzziness of parameters such as resource demand, scheduling time, and satisfaction, and designed the constrained parameter interval method to solve the optimal solution, which achieved the fast search of the Pareto optimal solution. [PERSON] [27] et al. proposed a bi-objective mixed integer linear programming (MILP) model for the allocation and scheduling of disaster relief units, based on robust optimization techniques for uncertainty sets and multiple choice goal programming (MCGP) with utility functions, verifying the high complexity of the problem and the significant effect of uncertainty on the solution. [PERSON] [28] et al. proposed a multi-period optimization model for EMA under uncertainty with the objectives of minimum time, minimum cost, and minimum risk. A cycle optimization model with stochastic and fuzzy constrained programming deterministic transformation methods and an improved genetic algorithm (IGA) were used to solve the proposed model, illustrating the relationship between risk, time, and cost, and the flexibility dimension in various optimized multi-cycle EMA scenarios. The existing resource allocation method is not suitable for the special railway transportation of dangerous chemicals. In order to make more reasonable use of resources, the resource allocation method in this paper is proposed. The main contributions of this paper are as follows:  
1. We propose an emergency response resource allocation model using the coal-to-oil railway transportation mode, which is used to allocate emergency rescue materials after the leakage of hazardous chemicals;
2. We propose an improved bee colony algorithm, which adds pre-allocation when initializing the population and improves the directional search ability of the population. In the multi-hazard coupled scenario of railway freight accidents involving hazardous chemicals, with the serious consequences and rapid development of such disasters, there is a lack of research on the existing emergency resource allocation methods for hazardous chemical railway transport accidents. On the basis of existing research, based on the determined location of rescue points, and according to the weight coefficients of various types of accidents, this paper allocates rescue materials according to the mode of rescue teams. With the goal of minimizing the time and cost of delivering rescue materials, the bee colony algorithm, genetic algorithm, and particle swarm algorithm are used to solve the objective function to obtain the optimal resource allocation scheme.