Application Of Improved Bee Colony Algorithm In Order Batching Problem

With the increasing competition in the market,the phenomenon of product homogenization is becoming more and more serious,and the role of logistics as the "third profit source" has become increasingly prominent.An efficient logistics system can help enterprises reduce logistics costs substantially.Warehousing and distribution operations is an important part of the logistics system,related research shows that human consumption picking accounted for the largest proportion of warehousing distribution operation,how to optimize the selection of operation has been the focus of many scholars.In picking operation,the picking distance is the largest proportion of manpower input in picking operation.It is a research direction to optimize order picking by dividing the needed order into batches and shortening the total picking distance with the same order.Based on this,this paper proposes an order batching method for single area warehouse,which takes into account the characteristics of picking vehicles and orders,and has certain advantages.In order to solve the order batch model,this paper attempts to introduce the concepts of "anti-learning" and other related theories to improve the traditional bee colony algorithm to improve the performance of the algorithm in order to get better batch results.In order to verify the validity of the batch,in the number of different orders of orders in batches using the improved bee colony algorithm,and based on the traditional channel similarity and gravity model order batching algorithm based on comparative validation,the experiments show that the improved bee colony algorithm can achieve good results in batch order both in small batch orders and in larger orders.Using improved bee colony algorithm to batch order can effectively avoid the shortcomings of the traditional algorithm based on channel similarity batch.At the same time,the batch time is better than the batch algorithm based on Gravity Model in batch order.Therefore in order large quantities of cases using improved ABC algorithm in the promotion of a certain significance to order,and also provide some reference for the significance of the batch algorithm.