考虑设施规模决策的两级选址-路径优化

Two echelon location-routing optimization considering facility sizing decision

针对目前电商行业基础设施布局和空间利用不合理的问题,提出考虑设施规模决策的两级选址-路径问题(2E-LRP)求解模型。首先,在传统2E-LRP中引入差异性设施规模约束,通过识别客户群设计不同设施规模组合,利用规模弹性变化调整总成本组成,并以最小运营成本为目标建立顾及设施规模弹性变化的2E-LRP模型;其次,提出两阶段混合迭代局部搜索启发式算法求解模型;最后,分析所提模型和优化算法,并以Prodhon等不同数据集为实例进行验证。实验结果表明,所提模型具有针对区域差异和不同数据规模的普适性,且设施规模的弹性变化范围值与总成本呈负相关;与拉格朗日松弛粒度禁忌搜索(LRGTS)等算法的最优成本相比,所提算法对所有算例的最优成本平均值降低了6.67%,可以有效节约运行成本。

A two Echelon Location-Routing Problem(2E-LRP)solving model considering facility sizing decision was proposed to address the issues of unreasonable infrastructure layout and space utilization in the existing e-commerce industry.Firstly,differential facility sizing constraints were introduced into the traditional 2E-LRP,different combinations of facility sizes were designed by identifying customer base,the total cost composition was adjusted by using changes in size,and a 2E-LRP model considering facility size change with the minimum operating cost as goal was established.Secondly,a two-stage hybrid iterated local search heuristic algorithm was proposed for solving the model.Finally,the performance of the proposed model and optimization algorithm were analyzed and verified with examples in different datasets such as Prodhon.Experimental results show that the proposed model is universal for regional differences and different data sizes,and there is an inverse relationship between the total cost and the change range of facility size.Compared with the optimal costs of algorithms such as Lagrangean Relaxation Granular Tabu Search(LRGTS),the average value of the optimal cost of the proposed algorithm on all instances is reduced by 6.67%,which can effectively save the operating cost.