Dynamic Order-Based Scheduling Algorithms for Automated Retrieval System in Smart Warehouses

Abstract

In typical e-commerce warehouse operations, upon receiving the orders from customers, the purchased items need to be retrieved from shelves and then packaged accordingly for delivery. To automate and speed up the item retrieval process, a Smart Warehouse usually employs a management system, called the Automated Retrieval System (ARS), to control and schedule the retrieval jobs. The working principle of ARS is crucial to the Smart Warehouse because it will have a great impact on the subsequent downstream processes. In short, all the items in a particular order should be considered as an integral part; if one of these items encounters a much larger retrieval delay than others do, then the entire order may experience an unnecessary latency. In the past, the integrality of order has not received much attention for the parallel retrieval process of multiple stackers. To take this into account, this paper proposes using an Order Tag to label all the items that belong to the same order for retrieval job scheduling. The way of calculating the Order Tags will then determine the scheduling discipline of the ARS. With the objectives of minimizing the average delay and ensuring the fairness, two algorithms are proposed. They are named as Dynamic Order-Based (DOB) and Dynamic Order-Based with Threshold (DOBT) Scheduling Algorithms, respectively. Compared with the First-Come-First-Serve and other approaches, the simulation results show that DOB and DOBT are able to reduce the average order retrieval delay by at least 30%, and generate less backlog pressure to the downstream operations.

Keywords

• Warehouse automation
• automated retrieval system
• order integrality
• job scheduling
• algorithm design and analysis