I am honored to be serving on the Board of Directors for the Warehousing Education and Research Council (WERC). WERC “offers resources that help distribution professionals stay at the leading edge including educational events, performance metrics for benchmarking, practical research, expert insights and peer-to-peer knowledge exchange.”
Order-Fulfillment is one of the most critical tasks in a distribution center (and one anyone who has purchased anything from an online distributor like Amazon has experienced first hand). My dissertation (under the direction of Russ Meller) developed models to analyze the piece-level order-fulfillment process in the pharmaceutical industry. Check out this video on how CVS Pharmacy ensures that medications are delivered to pharmacies through the use of order-fulfillment technologies. One such technology used in pharmaceutical distribution (as well as other industries) is an A-Frame System, which are pretty neat automated piece-level order-fulfillment technology. Check out this video on how Amazon uses a Random Storage Policy in their Order-Fulfillment Processes.
- The design of Distribution Centers requires answering a number of questions, such as where to store products, how to layout your facility, how to route order pickers to minimize travel, how much order picking technology should be used, what’s the throughput trade-offs based on different designs, etc. The correct answer to all these questions is “It depends”. It depends on a company’s constraints, objectives, environment, etc. Thus, my research team and I develop analytical models to provide insights into how to answer these types of questions for different environments. A few examples follow.
- Working with a leading warehouse technology company, we created a framework to inform selection of piece-level order fulfillment technologies. See my full blog post on our framework and analysis here. The academic citation is: Pazour, Jennifer A. and Meller, Russell D., 2014, “A Framework and Analysis to Inform the Selection of Piece-Level Order-Fulfillment Technologies,” Progress in Material Handling Research: 2014, Material Handling Institute, Charlotte, NC. (Download the PDF )
- My former Ph.D. student Faraz Ramtin and I have developed analytic models to study automated storage and retrieval systems (AS/RS) that have multiple I/O points in the aisle. Such systems are common in temperature controlled environments, such as grocery distribution centers. Here is a video of such systems used for case picking at the Walgreens warehouse in Anderson, South Carolina.
Faraz’s dissertation consists of three contributions all focusing on a special type of case-level order fulfillment technology – an “Automated Storage and Retrieval System with Multiple in-the-aisle pick positions.” These semi-automated systems are common in temperature-controlled warehouses. Our first contribution includes the first study to analyze AS/RS with multiple in-the-aisle outputs. We develop expected travel time models for random storage policies and provide design insights into these systems. In our second contribution, we considered the use of MIAPP-AS/RS to fulfill orders for non-identical items’ demand, which relaxed some of the assumptions we made in the first contribution. Specifically, we focused on an important practical design decision, the optimal SKU assignment problem. We studied the impact of different pick position assignments on system throughput, as well as system design trade-offs that occur when the system is running under different operating policies and different demand profiles. We developed optimization models to find the optimal assignment that minimizes the expected travel time. Finally, we developed optimization models for the SKU-to-pick position assignment problem for dedicated and class-based storage policy for MIAPP-AS/RS. By exploiting the structure of these optimization models, we decomposes the problem using Benders decomposition.
This resulted in the following citations:
- Ramtin F., Pazour J. A. “Analytical Models for an Automated Storage and Retrieval System with Multiple in-the-Aisle Pick Positions”. IIE Transactions, 46(9), 968-986.
- Ramtin F., Pazour J. A. 2015, “Product Allocation Problem for an AS/RS with Multiple in-the-Aisle Pick Positions”. IIE Transactions, 47(12) 1379-1396.
- Along with a research collaborator (Hector Carlo at University of Puerto Rico), we studied how to rearrange products in a distribution center when demand profiles change. If you grew up in a place with seasons, this is similar to reshuffling your winter coats towards the front of your closet in October and shorts toward the front in June. Warehouse reshuffling is a reorganization strategy that consists of repositioning items by moving them sequentially. This study investigates how to optimize warehouse reshuffling and quantifies the effect of common assumptions. A mathematical programming formulation for the general warehouse reshuffling problem, the complexity of the problem, several heuristics based on the problem structure, a formal proof delimitating instances where double-handling can be a productive move, and managerial insights on the performance of reshuffling policies in various environments are presented. Experimental results suggest that the proposed heuristics improve upon a benchmark heuristic by relaxing how cycles are handled and incorporating double-handling.
This resulted in the following citation:
- Who said distribution wasn’t all fun and games. Check out this story about how libraries battle for book-sorting championships.