Routing order pickers in a warehouse with a middle aisle

Roodbergen, Kees Jan; Koster, René de

doi:10.1016/s0377-2217(00)00177-6

Cited by 255 publications

(130 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Ratliff and Rosenthal (1983) use dynamic programming to find an optimal route for a rectangular, narrow aisles and single-block warehouse. De Koster et al (1998) and Roodbergen and De Koster (2001) extend the method for a warehouse where the I/O point location is decentralized and warehouses with a middle aisle (2 blocks). Instead of the optimal routing methods, heuristics are commonly used in practice because they are easy to implement and maintain.…”

Section: Literature Reviewmentioning

confidence: 99%

Performance approximation and design of pick-and-pass order picking systems

Koster

2008

IIE Transactions

Self Cite

View full text Add to dashboard Cite

In this paper, we discuss an approximation method based on G/G/m queuing network modeling using Whitt's (1983) queuing network analyzer to analyze pick-and-pass order picking systems.The objective of this approximation method is to provide an instrument for obtaining rapid performance estimates (such as order lead time and station utilization) of the order picking system. The pick-and-pass system is decomposed into conveyor pieces and pick stations.Conveyor pieces have a constant processing time, whereas the service times at a pick station depend on the number of order lines in the order to be picked at the station, the storage policy at the station, and the working methods. Our approximation method appears to be sufficiently accurate for practical purposes. It can be used to rapidly evaluate the effects of the storage methods in pick stations, the number of order pickers at stations, the size of pick stations, the arrival process of customer orders, and the impact of batching and splitting orders on system performance.Free Keywords pick-and-pass, order picking, warehousing, queuing network, simulation Availability The ERIM Report Series is distributed through the following platforms: AbstractIn this paper, we discuss an approximation method based on G/G/m queuing network modeling using Whitt's (1983) queuing network analyzer to analyze pick-and-pass order picking systems.The objective of this approximation method is to provide an instrument for obtaining rapid performance estimates (such as order lead time and station utilization) of the order picking system. The pick-and-pass system is decomposed into conveyor pieces and pick stations.Conveyor pieces have a constant processing time, whereas the service times at a pick station depend on the number of order lines in the order to be picked at the station, the storage policy at the station, and the working methods. Our approximation method appears to be sufficiently accurate for practical purposes. It can be used to rapidly evaluate the effects of the storage methods in pick stations, the number of order pickers at stations, the size of pick stations, the arrival process of customer orders, and the impact of batching and splitting orders on system performance.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Performance approximation and design of pick-and-pass order picking systems

Koster

2008

IIE Transactions

Self Cite

View full text Add to dashboard Cite

show abstract

“…There is a penalty to pay for inserting a middle cross aisle: it reduces floor space that could otherwise be allocated to storage, and therefore requires a slightly larger facility to maintain the same amount of storage. However, when more than one location is visited in a single tour, the addition of a cross aisle creates more possible routes for travel between locations and therefore has the potential to reduce expected travel [15]. For single-command travel, Layouts A and C are preferred, whereas Layouts B and C are generally preferred for dual-command travel [13].…”

Section: Introductionmentioning

confidence: 99%

Optimizing fishbone aisles for dual‐command operations in a warehouse

Pohl

Meller

Gue

2009

Naval Research Logistics

View full text Add to dashboard Cite

Unit-load warehouses store and retrieve unit-loads, typically pallets. When storage and retrieval operations are not coordinated, travel is from a pickup and deposit (P&D) point to a pallet location and back again. In some facilities, workers interleave storage and retrieval operations to form a dual-command cycle. Two new aisle designs proposed by Gue and Meller ("Improving the unit-load warehouse." In Progress in Material Handling Research: 2006. Material Handling Industry of America, Charlotte, NC, 2006) use diagonal aisles to reduce the travel distance to a single pallet location by approximately 10 and 20% for the two designs, respectively. We develop analytical expressions for travel between pallet locations for one of these-the fishbone design. We then compare fishbone warehouses that have been optimized for dual-command to traditional warehouses that have been optimized in the same manner, and show that an optimal fishbone design reduces dual-command travel by 10-15%.

show abstract

“…They found that Sshape heuristics perform well in the narrow-aisle high-bay pallet with many items scenario. Roodbergen and Koster [14] used dynamic programming to formulate the shortest traveling path for a warehouse with three cross aisles. Other research related to design and planning of warehousing systems can be found in Cormier and Gunn [15], Cormier [16], Van den Berg and Zijm [17] and Rouwenhorst et al [18].…”

Section: Literature Reviewmentioning

confidence: 99%

Warehouse Layout Design for an Automotive Raw Material Supplier

Phumchusri¹,

Kitpipit²

2017

View full text Add to dashboard Cite

Abstract. The case-study company faces the limited space situation. Thus, the company decides to uninstall their temporary warehouses and re-locate products in two permanent warehouses. The objective of this research is to design the layouts of the two permanent warehouses so that the spaces can be efficiently used and the total picking distance is low. The past data, Invoices and Stock Data, are used for developing layouts designing processes. This research involves the collecting of Product Size Data to calculate the required space for the products. There are two phases in layout designing process. The first phase is the product categories grouping. This phase categorizes product categories into two groups for the two warehouses. The second phase is the layouts designing. In this phase, the layouts of the two warehouses and the locations of the products are designed. According to the company requirements and policies, the Adapted Class-Based Turnover Assignment is adopted in order to design the layouts for the two warehouses. Layouts of the warehouses are designed, analyzed, and evaluated. The best layouts give the best trade-off between quantitative results, i.e., the total picking distance and the remaining space, and qualitative results, i.e., the usability and the product suitability. The designed layouts are applied in the case-study company. This research develops a systematic and practical layout designing method which is flexible and can be adopted in other warehouses.

show abstract

Routing order pickers in a warehouse with a middle aisle

Cited by 255 publications

References 6 publications

Performance approximation and design of pick-and-pass order picking systems

Performance approximation and design of pick-and-pass order picking systems

Optimizing fishbone aisles for dual‐command operations in a warehouse

Warehouse Layout Design for an Automotive Raw Material Supplier

Contact Info

Product

Resources

About