A risk assessment based optimization method for route selection of hazardous liquid railway network. (December 2018) - Zhang, Haoran; Yuan, Meng; Liang, Yongtu; Wang, Bohong; Zhang, Wan; Zheng, Jianqin
Highlights: A multi-objective optimization method for route selection of hazardous liquid railway network is proposed. A comprehensive risk assessment model is built considering multiple risk factors. A three-stage method coupling PSO, ACO and A-star algorithm is adopted to solve the problem. The practicality of the proposed method is verified through case study. Abstract: Route selection is the first and significant step for hazardous liquid railway network design project. Not only the economy, but the safety factors need to be considered for making a comprehensive analysis and determining an appropriate design plan. However, the railway network route selection is a complex multi-objective decision problem. Considering the construction cost and safety factors of hazardous liquid railway, this paper proposed a multi-objective optimization model. Considering the impact metrics, air pollution, river pollution, soil-underground water pollution, sensitive area and emergency system, a comprehensive risk assessment model was further built. The weight of each metric was decided by expert scoring. Based on index pricing method, risk factors were considered into maintenance and operation cost. Aiming at the strong non-linearity, a three-stage method was adopted to solve the problem. A virtual case and a real case with two refineries as sources and two terminals in midwestern China were studied in this paper. The construction schemes of hazardous liquid railway network in the study region were obtained by using the proposed method with considering the complex geographical and social environment. The effect of algorithm parameters on model was discussed in paper. Due to the high subjectivity of the emergency system score, the sensitivity of which was further analyzed. The practicality of the proposed method was verified through the case study.