Designing unit-load warehouses: Use deterministic or probabilistic models?

Mahmut Tutam, Jingming Liu, John A. White, Haitao Liao

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Designing a warehouse can be quite challenging because of the variability and uncertainty of operations performed. Although deterministic models can be developed and solved easily, they do not capture the random variation inherent in travel distances. In determining the optimal shape of a unit-load warehouse, will the designs be different if the shape is determined to minimize the average travel distance versus minimize the expected number of requests for storage and retrieval (S/R) waiting or being served? To answer this question, we compared the optimal shape factor and resulting expected travel distance for a multi-dock, unit-load warehouse under a new dwell-point policy. Compared to previous research, the performance of the system is increased approximately nine percent by using a specific dwell-point policy for S/R equipment. The impact of minimizing the variance of travel time on the optimal warehouse shape was also examined. Although queueing model provide additional information, the optimal shape factor for unit-load warehouse based on deterministic analysis is not significantly different from the optimal shape factor based on probabilistic analysis.

Original languageEnglish (US)
Title of host publicationIISE Annual Conference and Expo 2021
EditorsA. Ghate, K. Krishnaiyer, K. Paynabar
PublisherInstitute of Industrial and Systems Engineers, IISE
Number of pages6
ISBN (Electronic)9781713838470
StatePublished - 2021
Externally publishedYes
EventIISE Annual Conference and Expo 2021 - Virtual, Online
Duration: May 22 2021May 25 2021

Publication series

NameIISE Annual Conference and Expo 2021


ConferenceIISE Annual Conference and Expo 2021
CityVirtual, Online


  • General service times
  • Optimal shape factor
  • Poisson distributed arrivals
  • Queueing model
  • Unit-load warehouse

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering


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