A cloud-based location assignment system for packaged food allocation in e-fulfillment warehouse

Abstract

E-retailing is the delivery of products and services over the Internet, and it has been growing rapidly in recent years. Logistics services in the related warehouses have to be enhanced accordingly in order to handle the huge amount of e-orders in a shorter timeframe. Moreover, since the e-retailing of packaged food has been getting popular, these warehouses inevitably have to handle food products requiring special care, including temperature, humidity and insolation control, and expiry date management. Consequently, suitable storage guidelines have to be formulated for these warehouses to cope with their more demanding daily operations. A cloud-based location assignment system (CLAS) is thus proposed in this article, which provides timely and comprehensive solutions to the storage location assignment problem for warehouse operators. CLAS applies (i) cloud-based infrastructure for enhancing the agility of the proposed system, (ii) fuzzy association rule mining for predicting the potential storage time of various types of packaged food, and (iii) fuzzy logic and association rule mining for offering the most preferred storage locations of various products. A prototype of the CLAS is tested in a warehouse which involves packaged food handling. The test results show that the operational efficiency measured in terms of storage assignment decision-making time and order-picking time and the quality of the storage assignment solutions measured in terms of product disposal rate and product return/exchange rate have been improved in the case company.