A routing optimization with risk control and reduction provides a quantitative support for an efficient organization of the hazardous materials transportation where road-rail multimodal transportation plays an important role. Oriented on the viewpoint of the multimodal operator, this study investigates a hazardous materials routing problem for their door-to-door transportation through a road-rail multimodal hub-and-spoke network. It is difficult to determine the exact demand of hazardous materials for each transportation order during the advanced routing decision making. Therefore, demand uncertainty is introduced into the problem, in which the uncertain demands are modeled by triangular fuzzy numbers. To enhance the quality of service of the transportation, the hazardous materials routing optimization in this study uses fuzzy soft time windows to optimize the last-mile delivery of hazardous materials that determines the timeliness of transportation. Accordingly, this study proposes a fuzzy multi-objective routing model that is linear and considers the constraints of the customers' preferred service levels. To solve the proposed model, its crisp reformulation is first achieved by using the fuzzy expected value method and Jimenez's fuzzy ranking method. Then, the ε-constraint method is adopted by this study to obtain the Pareto frontier for the multiobjective optimization problem. Finally, an experimental case study is carried out to verify the proposed modeling of this study. By using sensitivity analysis and fuzzy simulation, the conflicting relationship among the economic, risk, reliability and timeliness objectives that improving one objective worsens the others is clearly indicated, and the insights that helps decision makers to make effective tradeoffs among these objectives to get a most suitable hazardous materials road-rail multimodal transportation plan are also summarized.