A travel-time model for a person-onboard order picking system

The design of an order picking system in a distribution center depends on several decisions, where a key decision is determining the optimal storage system configuration (the number, length, and height of the storage aisles). To make this decision, a throughput model that considers vertical, as well as horizontal, travel is needed. In this paper we extend prior research that considers horizontal travel for a given number and length of the storage aisles so that we are also able to consider the height of the aisles as well. Such a model will provide a more accurate estimate of the throughput of an order picker and it will also permit an examination of the tradeoff between the length and height of the aisles. The analytical model we develop to estimate throughput is based on probability models and order statistics results assuming random storage. It is intended for person-onboard order picking systems and we consider both Tchebychev and rectilinear travel. We illustrate the use of our travel-time model by incorporating it into a simple, cost-based optimization model to recommend the height of a one-pallet-deep storage system.

[1]  Gino Marchet,et al.  Optimal layout in low-level picker-to-part systems , 2000 .

[2]  Lars Medbo,et al.  A Methodology for Evaluation of Order Picking Systems as a Base for System Design and Managerial Decisions , 1994 .

[3]  Russell D. Meller,et al.  The effects of pick density on order picking areas with narrow aisles , 2006 .

[4]  Tho Le-Duc,et al.  Travel time estimation and order batching in a 2-block warehouse , 2007, Eur. J. Oper. Res..

[5]  Pratik J. Parikh Designing Order Picking Systems for Distribution Centers , 2006 .

[6]  H. Hwang *,et al.  An evaluation of routing policies for order-picking operations in low-level picker-to-part system , 2004 .

[7]  Edward H. Frazelle,et al.  Performance of miniload systems with two-class storage , 2006, Eur. J. Oper. Res..

[8]  Gunter P. Sharp,et al.  A structured procedure for analysis and design of order pick systems , 1996 .

[9]  Gunter P. Sharp,et al.  Example application of the cognitive design procedure for an order pick system: Case study , 1995 .

[10]  Marc Goetschalckx,et al.  Research on warehouse operation: A comprehensive review , 2007, Eur. J. Oper. Res..

[11]  Randolph W. Hall,et al.  DISTANCE APPROXIMATIONS FOR ROUTING MANUAL PICKERS IN A WAREHOUSE , 1993 .

[12]  Jeroen P. van den Berg,et al.  A literature survey on planning and control of warehousing systems , 1999 .

[13]  Charles J. Malmborg An integrated storage system evaluation model , 1996 .

[14]  Pratik J. Parikh,et al.  Estimating picker blocking in wide-aisle order picking systems , 2009 .

[15]  W. H. M. Zijm,et al.  Warehouse design and control: Framework and literature review , 2000, Eur. J. Oper. Res..

[16]  Loon Ching Tang,et al.  Travel time analysis for general item location assignment in a rectangular warehouse , 1999, Eur. J. Oper. Res..

[17]  Charles G. Petersen,et al.  A comparison of picking, storage, and routing policies in manual order picking , 2004 .

[18]  Pratik J. Parikh,et al.  Selecting between batch and zone order picking strategies in a distribution center , 2008 .

[19]  Iris F. A. Vis,et al.  A model for warehouse layout , 2006 .

[20]  Yavuz A. Bozer,et al.  Travel-Time Models for Automated Storage/Retrieval Systems , 1984 .

[21]  Charles J. Malmborg,et al.  An integrated performance model for orderpicking systems with randomized storage , 2000 .

[22]  Byung Chun Park Performance of automated storage/retrieval systems with non-square-in-time racks and two-class storage , 2006 .

[23]  Enrique Castillo Extreme value theory in engineering , 1988 .