A multi-dock, unit-load warehouse design

Abstract

Expected distance formulations are developed for a rectangle-shaped, unit-load warehouse having dock doors along one warehouse wall. Based on dock-door configurations treated in the literature and/or used in practice, three scenarios are considered: (i) equally spaced dock doors spanning a wall; (ii) equally spaced dock doors with a specified distance between adjacent dock doors, and an equal number of dock doors located on each side of the wall’s centerline; and (iii) equally spaced dock doors with a specified distance between adjacent dock doors and the first dock door located a given distance to the right of the left wall. Defining the shape factor as the warehouse width divided by its depth, the shape factor minimizing expected distance is determined. Single- and dual-command travel results from discrete formulations are compared with results from closed-form expressions using continuous approximations. The optimal shape factor depends on the number and locations of dock doors. When the distance between adjacent dock doors is a function of the warehouse’s width, previous research results are confirmed. However, when distances between adjacent dock doors are specified, our results differ from a commonly held belief the optimal shape factor is always less than or equal to 2.0.

KEYWORDS:

• Multiple dock doors
• shape factor
• unit-load
• single-command
• dual-command

Acknowledgements

The authors wish to thank the referees for their comments which improved the article significantly. Also, they express their appreciation to the Turkish Ministry of National Education for its support of the research.

Additional information

Notes on contributors

Mahmut Tutam

Mahmut Tutam is an assistant professor in the Department of Industrial Engineering at Erzurum Technical University in Turkey, and holds a BSIE degree from Gazi University in Turkey. In 2012, he was awarded a full scholarship from the Ministry of National Education of Turkey to study in the United States. He received his MSIE and Ph.D. from the University of Arkansas in 2015 and 2018, respectively. He performs research on facility logistics and warehouse design problems. A recipient of the 2015 ISERC Best Track Paper in Facility Logistics award, he has given multiple presentations and served as Session Chair at IISE and INFORMS annual meetings. Selected for the 2017 Material Handling Teachers Institute, he is the initial recipient of an Award for Outstanding Service from the UA Graduate School and International Education.

John A. White

John A. White is a distinguished professor of Industrial Engineering and chancellor emeritus at the University of Arkansas. He received his BSIE, MSIE and Ph.D. degrees from the University of Arkansas, Virginia Tech, and The Ohio State University, respectively. He formerly served on the faculties of Virginia Tech and Georgia Tech for 8 years and 22 years, respectively. After serving as dean of engineering at Georgia Tech for 6 years, he returned to his undergraduate alma mater and served as its chancellor for 11 years, stepping down and returning full time to the UA faculty in 2008. His publications include six co-authored text books three of which received Book of the Year awards from IISE. Past President of IISE, he is a Fellow of ASEE, IISE, and INFORMS. A member of the National Academy of Engineering, he is the recipient of numerous awards, including IISE’s highest award, the Frank and Lilian Gilbreth Award. Over his career, he has served on five boards of directors for publicly traded corporations: Eastman Chemical Company, J. B. Hunt Transport Service, Inc., Logility, Inc., Motorola (Motorola Solutions), Inc., and Russell Corporation.