Research On Order Scheduling Optimization Method Of Automatic Sorting System

Due to the large differentiation of orders in logistics distribution centers,it is difficult to improve the degree of automation of sorting operations,which has become a key factor restricting the efficiency of logistics distribution.Therefore,it has become an important goal of logistics center management to effectively optimize the operation process of order picking and improve operation efficiency.In this paper,based on the automatic sorting system of "goods to person" mode,combined with domestic and foreign research results on this problem,aiming at the problems such as unbalanced order allocation and unreasonable material carrier in the process of order scheduling,the picking process was analyzed and optimized from the two stages of order batch and vehicle combination:(1)Analyze the picking process of "goods to person" mode and construct the corresponding mathematical model.The objective function is to minimize the total number of cargo handling,choose order batch strategy based on clustering algorithm for optimization.Dividing the order into different lots and picking simultaneously reduces the time required to process the order.Finally,the effectiveness of the proposed algorithm is proved by comparing with other order batch strategies,such as FCS and genetic algorithm.And it is found that the clustering algorithm based on cosine similarity has the best optimization effect on this problem through data analysis.(2)After selecting a reasonable strategy to divide the order into batches,this paper makes a further study on how to select the appropriate carrier combination based on the batch results,according to the actual background that a material is stored in multiple places and the storage rules that multiple materials are stored in a single cargo unit.The breadth-first search algorithm is used to construct a "solution tree" to search the solution space of the problem.Take the carrier handling times as the measurement index,and design a reasonable pruning function to improve the efficiency of the algorithm.Then the optimal vehicle combination scheme was obtained.Finally,an appropriate data set is used to conduct experiments,which shows that the breadth-first search algorithm applied to the vehicle combination problem can greatly reduce the times of vehicle handling and effectively improve the picking efficiency.