Effective placement of dangerous goods cars in rail yard marshaling operation

Abstract

Train derailments are important safety issues, and they become even more critical when dangerous goods (DG) are involved. This paper is concerned with mitigating derailment risk through improved operational strategies, with a specific focus on DG marshalling practices in the train-assembly process. A new modelling framework is proposed to investigate how the position of DG railway cars affects their chances of being involved in a derailment as the train travels over a given track segment. The underlying research problem can be formulated as a linear integer programming technique. However, since solving this formulation is computationally intractable, a heuristic method has been developed based on a genetic algorithm that gives a near-optimum solution. The proposed model is applied to a hypothetical rail corridor to demonstrate how effective marshalling of DG along a train can reduce overall derailment risks.