Similarity coefficients and clustering techniques for the correlated assignment problem in warehousing systems

Picking operations are carried out by a great many large and medium sized companies belonging to a large number of industrial and service sectors, such as the apparel industry, the food sector, wood furniture production and logistic outsourcing providers. Furthermore the recent growth in e-commerce and the strength of its development have brought a new focus on warehousing activities and facilities, in particular on the management of Order Picking Systems (OPS): fulfillment centres need to process a far higher volume of smaller orders which increases logistics costs. In warehouse and distribution centres based on picking activities, the products have to be picked from a set of specific storage locations by an order picking (OP) process usually driven by customer orders. Products that are frequently ordered together in multi item orders should be stored near each other: this is the correlated assignment strategy. Literature presents several studies of storage location strategies, but only a little discussion on the opportunity for correlated assignment. The aim of this study is to develop, test and compare a set of different storage allocation rules based on the application of original similarity coefficients and clustering techniques. The illustration of a case study demonstrates the efficacy of the obtained results by the application of the idea that items often ordered together should be located near to each other.