摘要
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.
出处
《中国安全科学学报》
CAS
CSCD
北大核心
2015年第10期84-90,共7页
China Safety Science Journal
基金
国家自然科学基金资助(61364026
51408288)
兰州交通大学校青年基金资助(2015026)
兰州市科技计划项目(2014-1-172)
关键词
物流工程
危险品运输
多目标优化
车辆路径问题
概率模型
logistics engineering
hazardous materials(hazmats) transportation
multi-objective optimization
vehicle routing problem
probabilistic model