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

Authored by Raymond R. Hill, Brian L. Heath, Frank W. Ciarallo

Date Published: 2013-07

DOI: 10.1007/s00170-012-4505-5

Sponsors: No sponsors listed

Platforms: AnyLogic

Model Documentation: Other Narrative

Model Code URLs: Model code not found

Abstract

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 (TM) and the simulation is constructed using the simulation software AnyLogicA (R). 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.

Tags

Simulation Agent-based modeling Congestion Warehouse Distribution center