This paper solves a routing problem of multi-hazmat railcars with consolidation operations in order to avoid serious consequences of hazmat accidents. We develop a bi-level optimization model for this problem, and apply a value-at-risk (VaR) approach to generate route choices. By incorporating the consolidation operations performed among different railway shipments, both the risks incurred at yards and on service legs are integratively quantified to evaluate route risks. Due to the inherent complexity of the problem, we propose an exact algorithm as well as a heuristic algorithm to solve the proposed model, and conduct extensive numerical experiments on instances generated from a real railway system in the Midwestern United States. The analysis shows that risk-seeking decision makers will benefit from consolidated transportation due to its potential to significantly reduce total transportation costs. As decision makers become more risk averse, i.e., confidence level increases, increasing the number of train services and reducing the amount of hazmat railcars and consolidation operation has a positive impact on reducing route risk. In addition, the computational results verify the effectiveness of our proposed optimization model and solution approaches, which can generate various routing plans for railway companies under different risk preferences, and our proposed heuristic algorithm gives an optimal or near-optimal solution in 1.41% to 28.22% of the time required by the exact algorithm.

中文翻译：

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基于风险值的多危险品轨道车路径问题方法


本文通过整合操作解决了多危险品轨道车的路线问题，以避免危险品事故的严重后果。我们针对这个问题开发了一个双层优化模型，并应用风险价值（VaR）方法来生成路线选择。通过整合不同铁路货物之间的拼箱作业，对场站和服务段的风险进行综合量化，评估线路风险。由于问题固有的复杂性，我们提出了精确算法和启发式算法来解决所提出的模型，并对美国中西部真实铁路系统生成的实例进行了广泛的数值实验。分析表明，寻求风险的决策者将受益于整合运输，因为它有可能显着降低总运输成本。随着决策者变得更加厌恶风险，即信心水平提高，增加列车服务的数量并减少危险品铁路车的数量和整合运营对降低路线风险具有积极的影响。此外，计算结果验证了我们提出的优化模型和求解方法的有效性，可以为不同风险偏好下的铁路公司生成各种路线计划，并且我们提出的启发式算法给出了1.41％至28.22的最优或接近最优解。精确算法所需时间的%。