时变温度下考虑装载策略的多温共配优化研究

The Multi-Temperature Joint Distribution Routing Optimization Considering Loading Strategy and Time-Varying Temperature

为了解决考虑外界温度变化、时间窗约束、装载策略的医药冷链多温共配车辆路径问题,建立了时变温度下考虑二维装载约束和多温层的VRPTW模型。考虑时变温度对热量损失的影响,确定制冷成本的度量函数;对于多温层共配,将有多种温层需求的客户点看作多个距离为零的单种温层需求的客户点集合;为提高装卸效率减少热量损失,改进左下角填充算法中装箱位置点的确定方法,混合遗传算法与大邻域搜索算法,根据模型特征在遗传算法中增加移出和重插入操作,设计改进左下角填充-遗传大邻域搜索算法对模型进行求解。最后结合算例,验证该模型和方法的有效性、正确性。

In order to solve the multi-temperature joint distribution vehicle routing problem of pharmaceutical cold chain considering the external temperature change,time windows constraint and loading strategy,a vehicle routing problem with time windows model considering time-varying temperature,two-dimensional loading constraint and multiple temperature layers is established.Considering the influence of time-varying temperature on heat loss,the measurement function of refrigeration cost is determined.For multi-temperature joint distribution problem,the customers with multiple temperature layers requirements are regarded as a set of customers with single temperature layer requirements with zero distance.To improve loading and unloading efficiency and reduce heat loss,the method to determine the packing position in the bottom-left-fill algorithm is improved.And the genetic algorithm and large neighborhood search algorithm are mixed,according to the characteristics of the model,the remove and reinsert operations are added to the genetic algorithm,and an improved bottom left fill-genetic-large neighborhood search algorithm is designed to solve the model.Finally,the validity and correctness of the model and method are verified by an example.