不确定条件下危险品运输径路研究

Study on Dangerous Goods Transportation Considering Road Network Traffic Volume

危险品运输过程中,外界因素的干扰会导致事故发生后影响人口数和运输时间的不确定性,此外路网交通量也会对运输风险产生影响。针对以上问题,开展了影响因素不确定性的危险品运输径路研究。首先,采用模糊理论确定了以运输风险、运输时间和运输成本最小为优化目标;设置了最大风险阈值的机会约束,构建了有时间窗约束的多目标优化模型。其次,考虑到均衡调整拥挤距离可以扩大解空间的搜索范围,设计了改进的NSGA-II算法对模型进行求解。最后,基于苏州地区的综合运输路网展开实例研究,验证了模型的可行性与算法的有效性,并对模型参数进行扰动分析。结果表明:在危险品运输过程中,路网交通量对其运输风险影响较大,在模型中加入路网交通量的影响因素,更加符合运输实际;另外,风险回归系数应根据道路实际情况进行合理取值,同时,模型求解结果可为不同偏好和综合偏好的运输决策者提供决策支持。

During the transportation of dangerous goods,the interference of external factors will lead to the uncertainty of affecting the population and transportation time after the accident,and the traffic volume of the external road network will also affect the transportation risk.In view of the above problems,the research on the transportation of dangerous goods with uncertain influencing factors is carried out.Firstly,using fuzzy theory,the optimization objective is to minimize transportation risk,transportation time and transportation cost;Set the opportunity constraint of the maximum risk threshold,and build a multi objective optimization model with time window constraint.Then,considering that equilibrium adjustment of congestion distance can expand the search range of solution space,an improved NSGA-Ⅱalgorithm is designed to solve the model.Finally,based on the comprehensive transportation network in Suzhou,an example is carried out to verify the feasibility of the model and the effectiveness of the algorithm,and the disturbance analysis of the model parameters is carried out.The results show that in the process of dangerous goods transportation,the traffic volume of the road network has a great impact on its transportation risk.Adding the influencing factors of the traffic volume of the road network into the model is more in line with the actual transportation.In addition,the risk regression coefficient is reasonably selected according to the actual situation of the road.At the same time,the model solution results can provide decision support for transportation decision makers with different preferences and comprehensive preferences.