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An agent-based modeling approach to analyze the impact of warehouse congestion on cost and performance


This article discusses a novel agent-based modeling (ABM) approach to analyze the impact of warehouse congestion and presents results indicating the significant effect of congestion on cost and performance in various scenarios. In particular, the simulation represents the behaviors of the order pickers in a picker-to-part, low picking warehouse and focuses on representing the traffic and movements of the pickers. The key motivation for simulating this system is the lack of literature discussing models or simulations capable of representing the congestion component of order pickers, a component important in actual warehouse operations. The conceptual model of the simulation is described and justified using the Conceptual Model for Simulation Diagram™ and the simulation is constructed using the simulation software AnyLogic®. The simulation is operationally validated via a series of experiments performed to test the simulation’s results against the expected dynamics of the system as described in (Tompkins et al. 2003). After operationally validating the simulation, key results are discussed and it is shown that the ABM simulation paradigm is capable of quantitatively capturing new and traditionally difficult to explore dynamics in warehouse operations, including components of congestion not considered in literature.

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Correspondence to Brian L. Heath.

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Article note

The views expressed in this article are those of the authors and do not necessarily reflect the official policy or position of the US Air Force, the Department of Defense, or the US Government. No endorsement intended.



The CM4S Diagram for this simulation is available for download at

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Heath, B.L., Ciarallo, F.W. & Hill, R.R. An agent-based modeling approach to analyze the impact of warehouse congestion on cost and performance. Int J Adv Manuf Technol 67, 563–574 (2013).

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  • Agent-based modeling
  • Distribution center
  • Warehouse
  • Congestion
  • Simulation