(An) order batching algorithm based on similarity coefficeint

Abstract

The order picking process, the process of retrieving products from specified storage locations on the basis of customer orders, is known to be the most laborious of all warehouse processes. Grouping of customer orders in a warehouse order (batching), and sequencing the items on a warehouse order to be retrieved (routing) are closely related with the efficiency of order picking process. This thesis deals with the order batching problem considering four different routing policies that have been frequently appeared in the literature. They are traversal routing policy, return routing policy, midpoint routing policy, and largest gap routing policy. Taking into account of the characteristic of each routing policy, we develop similarity coefficients for pairs of orders and then propose efficient order batching algorithms. To evaluate the performance of the algorithms, they are compared with an existing algorithm in terms of the total travel time and number of batches grouped. The computational results show that the proposed algorithms in general outperform the existing one except the case with the largest gap routing policy.