基于数字孪生技术的危化品车辆运输路径优化方法

针对危化品物流管控成本高、安全隐患检测困难、不确定因素较多等特点,基于数字孪生技术,建立孪生数据驱动下的危化品物流配送系统整体框架,实现对驾驶员疲劳状态及车辆故障预警等参数的实时监测。根据物理参数实现对危化品车辆调度物理空间的精准模拟与迭代优化。构建单一配送中心,带有时间窗约束的路径优化模型,以配送总成本最小为目标函数,结合孪生数据动态调整客户服务时间,采用遗传算法内核利用MATLAB求解数学模型。该方法有效解决了危化品物流调度过程中由于动态不安全因素对危化品运输成本带来的波动。

Vehicle transport path optimization method of hazardous chemicals based on digital twin technology

Aiming at the characteristics of the high cost of hazardous chemicals logistics control, the difficulty in detecting potential safety hazards and many uncertain factors, an overall framework of a hazardous chemicals logistics distribution system driven by twin data was established based on digital twin technology, which can realize the real-time monitoring of parameters such as fatigue status of drivers and fault warning of vehicles. Therefore, accurate simulation and iterative optimization of the physical space of hazardous chemical vehicle scheduling could be realized based on physical parameters. Besides, a path optimization model with time window constraints for a single distribution center was constructed. The minimum total cost of distribution was taken as the objective function and the customer service time was dynamically adjusted by combining twin data, and the mathematical model was solved by using Matlab tools with the genetic algorithm kernel. The fluctuations in the transportation cost of hazardous chemicals caused by dynamic unsafe factors in the logistics scheduling process can be effectively solved by adopting this method.