不确定环境下的危险品运输车辆路径优化  

Route Optimization of Hazardous Materials Transportation Vehicles in Uncertain Environment

作　　者：王琴 杨信丰[1] 李楠 李平 方晟浩 WANG Qin;YANG Xinfeng;LI Nan;LI Ping;FANG Shenghao(School of Transportation,Lanzhou Jiaotong University,Lanzhou 730070,China;Lanzhou Communication Section of China Railway Lanzhou Bureau Group Co.,Ltd.,Lanzhou 730030,China)

机构地区：[1]兰州交通大学交通运输学院,兰州730070 [2]中国铁路兰州局集团有限公司兰州通信段,兰州730030

出　　处：《计算机工程与应用》2022年第15期309-316,共8页Computer Engineering and Applications

基　　金：甘肃省教育厅“双一流”重点科研项目(GSSYLXM-04)。

摘　　要：针对非满载危险品运输车辆路径优化问题,通过模糊变量刻画运输过程中的人口密度、行驶速度与运输时间以及客户需求量等方面的不确定因素,考虑载货量变化对风险评估的影响,建立基于动态载货量的风险评估模型,以运输总风险、车辆总行程、车辆使用数最小为优化目标,同时兼顾时间窗、事故概率、载货量等约束构建了不确定环境下的危险品运输车辆路径多目标优化模型。将NSGA-Ⅱ算法与LNS算法相结合,设计混合NSGA-Ⅱ算法求解模型。结果表明,混合NSGA-Ⅱ算法可以获得空间分布均匀且收敛性较好的Pareto解集,不同运输参与者可根据自身偏好在解集中选择相应的配送方案;该算法得到的最优总风险、总行程及车辆使用数目分别比NSGA-Ⅱ算法优化了11.5%、1.0%和14.3%,算法搜索性能和求解精度明显提高。Aiming at the route optimization problem of non-fully loaded hazardous material transportation vehicles in uncertain environment, the uncertain factors in the transportation process are described by fuzzy variables, and considering the impact of cargo volume change on risk assessment, a risk assessment model based on dynamic cargo volume is established. The optimization objectives are to minimize the total risk of transportation, the total travel of vehicles and the number of vehicles used, taking into account the time window based on the constraints of accident probability and load capacity,a multi-objective optimization model of hazardous material transportation vehicle route in uncertain environment is constructed. Combining NSGA-Ⅱ algorithm with LNS algorithm, a hybrid NSGA-Ⅱ algorithm solution model is designed.The results show that the hybrid NSGA-Ⅱ algorithm can obtain the Pareto solution set with uniform spatial distribution and good convergence, and different transportation participants can choose the corresponding distribution scheme in the solution set according to their own preferences. The optimal total risk, total journey and number of vehicles obtained by the algorithm are 11.5%, 1.0% and 14.3% better than NSGA-Ⅱ algorithm respectively. The search performance and solution accuracy of the algorithm are significantly improved.

关 键 词：危险品运输 不确定环境 动态载货量 混合NSGA-Ⅱ算法 路径优化 

分 类 号：TP391[自动化与计算机技术—计算机应用技术] U491[自动化与计算机技术—计算机科学与技术]