Design and Control of Warehouse Order Picking: a literature review

Order picking has long been identified as the most labour-intensive and costly activity for almost every warehouse; the cost of order picking is estimated to be as much as 55% of the total warehouse operating expense. Any underperformance in order picking can lead to unsatisfactory service and high operational cost for its warehouse, and consequently for the whole supply chain. In order to operate efficiently, the orderpicking process needs to be robustly designed and optimally controlled. This paper gives a literature overview on typical decision problems in design and control of manual order-picking processes. We focus on optimal (internal) layout design, storage assignment methods, routing methods, order batching and zoning. The research in this area has grown rapidly recently. Still, combinations of the above areas have hardly been explored. Order-picking system developments in practice lead to promising new research directions.Order picking;Logistics;Warehouse Management

An Integrated Strategy for a Production Planning and Warehouse Layout Problem: Modeling and Solution Approaches

We study a real-world production warehousing case, where the company always faces the challenge to find available space for their products and to manage the items in the warehouse. To resolve the problem, an integrated strategy that combines warehouse layout with the capacitated lot-sizing problem is presented, which have been traditionally treated separately in the existing literature. We develop a mixed integer linear programming model to formulate the integrated optimization problem with the objective of minimizing the total cost of production and warehouse operations. The problem with real data is a large-scale instance that is beyond the capability of optimization solvers. A novel Lagrangian relax-and-fix heuristic approach and its variants are proposed to solve the large-scale problem. The preliminary numerical results from the heuristic approaches are reported

Using Agent Base Models to Optimize Large Scale Network for Large System Inventories

The aim of this paper is to use Agent Base Models (ABM) to optimize large scale network handling capabilities for large system inventories and to implement strategies for the purpose of reducing capital expenses. The models used in this paper either use computational algorithms or procedure implementations developed by Matlab to simulate agent based models in a principal programming language and mathematical theory using clusters, these clusters work as a high performance computational performance to run the program in parallel computational. In both cases, a model is defined as compilation of a set of structures and processes assumed to underlie the behavior of a network system

Design and Control of Warehouse Order Picking: a literature review

Order picking has long been identified as the most labour-intensive and costly activity for almost every warehouse; the cost of order picking is estimated to be as much as 55% of the total warehouse operating expense. Any underperformance in order picking can lead to unsatisfactory service and high operational cost for its warehouse, and consequently for the whole supply chain. In order to operate efficiently, the orderpicking process needs to be robustly designed and optimally controlled. This paper gives a literature overview on typical decision problems in design and control of manual order-picking processes. We focus on optimal (internal) layout design, storage assignment methods, routing methods, order batching and zoning. The research in this area has grown rapidly recently. Still, combinations of the above areas have hardly been explored. Order-picking system developments in practice lead to promising new research directions

Algorithms for dynamic forward area allocation in a warehouse

This thesis consists of two major parts. The first part is the presentation of two dynamic algorithms and the second part is the performance analysis of these algorithms using a real order data. In this study, two algorithms, Slot-based Dynamic Algorithm and Order-based Dynamic Algorithm are developed for dynamic forward area allocation. Both algorithms are based on the idea of reassignment of most profitable items to the forward pick area. For Slot-based Algorithm, the profitable item is selected whenever slot becomes empty. This decision criterion is changed in Order-based Algorithm and becomes the end of definite order cycle. This thesis attempts to determine savings gained by implementing two algorithms in various warehouse settings. Instead of savings, number of forward picks, replenishments between reserve and forward areas and finally number of stock outs are analyzed as performance measures. Earlier research focused mainly on the relocation of items only in the forward area according to the changing item popularity. On the other hand, our study addresses the issue of reassignment of items from reserve to forward slots in a volatile market environment. Additionally, the forward area is assumed to be a physical space consisting of slots, which makes our proposed algorithms convenient for real life applications. Our study provides interesting insights in order to increase warehouse efficiency. We observe the advantages and disadvantages of both algorithms in different warehouse settings. We believe that these insights help managers to select the robust methods for creating forward area allocations

A storage assignment problem with multi-stop picking tours in an automotive spare parts warehouse

Ankara : The Department of Industrial Engineering and Tte Institute of Engineering and Science of Bilkent University, 2008.Thesis (Master's) -- Bilkent University, 2008.Includes bibliographical references leaves 76-79.In this study, a storage assignment problem for an automobile spare parts warehouse is considered. Incoming items from the suppliers are located at storage slots in pallet loads with single stop storage tours while outgoing items requested from the company’s service centers are collected on a daily basis with multi-stop pick tours. The problem involves seeking a layout (defined by an assignment of items to storage slots) to minimize the total distance items are moved from the receiving dock to storage slots and from storage slots to the shipping dock. The items requested each day are not the same. Consequently, the number and locations of pick stops in pick tours differ from day to day. This feature of the problem sufficiently complicates the structure to make analytical approaches difficult to use. Two simulation models are developed, one single-level and one multi-level model, to investigate factors that have some effect on the storage assignment problem under consideration. Various insights are obtained for a set of storage assignment alternatives for both models.Aybar, EsraM.S

Intentional fragmentation for material storage

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2004.Includes bibliographical references (p. 165-167).A novel technique (location-relaxed storage) of mixing products within warehouse storage bins is presented and evaluated. Analyses of warehouse operations, storage space efficiency, error sensitivity, and placement policies are presented and compared to traditional warehousing techniques. The major factors that drive the performance differences between traditional, highly organized storage and location-relaxed storage are shown to include the number of unique stock keeping units (SKUs) served by the warehouse and the picking lot size characteristic of demand. The analyses demonstrate traditional storage techniques have greater difficulty dealing with a large SKU base. Furthermore, location-relaxed storage is shown to have a lower sensitivity to operation errors and a greater opportunity for cost savings through optimization opportunities. Finally, a new placement strategy especially suited for location-relaxed storage is presented. As the popularity of Radio Frequency Identification (RFID) increases and the technical issues of widespread RFID implementation are addressed, new applications of RFID technology will change the way the world operates. An ongoing, industry-wide effort to implement RF-tags throughout the material goods supply chain has the support of manufacturers, retailers, and technology companies. RFID in the supply chain represents an enabling technology that will allow warehouse operations to break away from traditional methodologies and adopt revolutionary techniques, such as location-relaxed storage.by Stephen Ho.Ph.D

Design and Control of Efficient Order Picking Processes

Binnen een logistieke keten dienen producten fysiek te worden verplaatst van de ene locatie naar de andere, van producenten naar eindgebruikers. Tijdens dit proces worden producten gewoonlijk opgeslagen op bepaalde plaatsen (magazijnen) voor een bepaalde periode. Orderverzameling – het ophalen van producten uit de opslaglocatie in het magazijn naar aanleiding van een specifieke klantorder – is het meest kritieke magazijnproces. Het is een arbeidsintensieve operatie in handmatig bestuurde systemen, en een kapitaalintensieve operatie in geautomatiseerde systemen. Een niet optimaal functionerend orderverzamelingsproces kan leiden tot onbevredigende service en hoge operationele kosten voor het magazijn, en dientengevolge voor de hele keten. Om efficiënt te kunnen functioneren dient het orderverzamelingsproces robuust te zijn ontworpen en optimaal te worden bestuurd. Dit proefschrift heeft als doel analytische modellen te ontwerpen die het ontwerp en de besturing van efficiënte orderverzamelingsprocessen ondersteunen. Verschillende methoden worden voorgesteld voor het schatten van de route langs de locaties van de te verzamelen producten, het bepalen van de optimale grenzen van zones in het magazijn die bestemd zijn voor opslag, de indeling van het magazijn, het aantal producten die tegelijk (in één ronde) worden verzameld (de batch size) en het aantal zones in het magazijn die worden ingericht voor het verzamelen en gereedmaken van orders. De methoden worden getest middels simulatie experimenten en worden inzichtelijk gemaakt met behulp van rekenexperimenten.Tho Le-Duc was born in 1974 in Quang Ninh, Vietnam. He received a Bachelor degree in Navigation Science from the Vietnam Maritime University in 1996 and a Postgraduate Diploma in Industrial Engineering from the Asian Institute of Technology Bangkok Thailand (AIT) in 1998. Thanks to the financial support from the Belgian Development and Co-operations, he obtained his master degree in Industrial Management from the Catholic University of Leuven in 2000. Since May 2001, he started as a Ph.D. candidate (AIO) at the RSM Erasmus University (formerly Rotterdam School of Management/Faculteit Bedrijfskunde), the Erasmus University Rotterdam. For about more than four years, he performed research on order picking in warehouses. As the results, Tho Le-Duc has been presented his research at several conferences in the fields of operations research, material handling, logistics and supply chain management in both Europe and North America. His research papers have been published or accepted for publication in several refereed conference proceedings, scientific books and international journals.Within a logistics chain, products need to be physically moved from one location to another, from manufacturers to end users. During this process, commonly products are buffered or stored at certain places (warehouses) for a certain period of time. Order picking - the process of retrieving products from storage (or buffer area) in response to a specific customer request - is the most critical warehouse process. It is a labour intensive operation in manual systems and a capital intensive operation in automated systems. Order picking underperformance may lead to unsatisfactory service and high operational cost for the warehouse, and consequently for the whole chain. In order to operate efficiently, the order picking process needs to be designed and optimally controlled. Thesis Design and Control of Efficient Order Picking Processes aims at providing analytical models to support the design and control of efficient order picking processes. Various methods for estimating picking tour length, determining the optimal storage zone boundaries, layout, picking batch size and number of pick zones are presented. The methods are tested by simulation experiments and illustrated by numerical examples

Enhancing Warehouse Performance by Efficient Order Picking

This thesis studies order picking in warehouses. Order picking, the process of retrieval products from their storage locations to fill customer orders, is regarded as the most critical operation in a warehouse. Using stochastic modelling, we develop a model to estimate order picking system performance on various design alternatives and operating policies. The model is fast, flexible, and sufficiently accurate for practical purposes. The thesis introduces a concept of Dynamic Storage. In a Dynamic Storage System (DSS), orders are picked in batches and only those products needed for the current pick batch are retrieved from a reserve area and are stored in the pick area, just in time. Through analytical and simulation models, we demonstrate a DSS can substantially improve order throughput and reduce labour cost simultaneously over conventional order picking systems, where all the products required during a pick shift are stored in the pick area. The thesis also studies an internal distribution process at a flower auction company. Based on simulation and optimization models, we propose ways to reduce congestion and improve order lead time