危险品运输车辆路径问题的多目标优化

Multi-objective optimization of hazardous materials transportation vehicle route problem

为保障危险品安全运输的同时实现运输成本最小化,采用多目标优化方法确定危险品运输车辆的最佳行驶路径。通过简化运输车辆经过人口密集区域风险因素的量化过程,以车辆数最少、运输总距离及经过人口密集区域行驶距离最短为目标,建立危险品车辆运输路径问题优化模型,并针对模型设计基于概率模型的多目标进化算法。以一个有25个需求节点及6个人口密集区域的危险品运输网络为例,验证模型和算法。算例结果表明,用该算法能够获得车辆路径问题的Pareto解,为危险品运输车辆调度提供决策支持。

For safety control in hazardous materials transportation with minimized transport-costs,a multi-objective optimization method was built to obtain reasonable traveling paths. By simplifying the risk factors quantization process of transport vehicles through population-dense area,an optimization model was built with consideration of the amount of vehicles,total transportation distance and the distance traveled through population-dense area as the objectives,and a multi-objective evolutionary algorithm was designed based on the probability model. The model and algorithm were verified with the simulation of the hazardous materials transport network with 25 demand nodes and 6 population-dense regions. The results show that the algorithm can be used to obtain the Pareto solution,which would provide decision support for hazardous materials transport vehicle scheduling.