Title: Analytical approximations to predict order picking times at a warehouse

Authors: Maria Hulett; Purushothaman Damodaran

Addresses: Department of Management Science, University of Miami, Miami, Florida 33124, USA ' Department of Industrial and Systems Engineering, Northern Illinois University, DeKalb, Illinois 60115, USA

Abstract: The primary objective of this research was to develop analytical approximations to predict the time taken to complete a customer order in a warehouse. The problem under study was modelled as a network of queues and the parametric decomposition approach was adopted to develop the approximations. Under this method, the queuing network is decomposed into individual queues allowing to analyse single (i.e., customer order processing, pallet building, and re-pick process) and fork-join stations (i.e., order picking with synchronisation constraints) within the same framework. Analytical formulations to estimate order picking times were developed and compared with equivalent simulation models to estimate the accuracy of the formulations. Appropriate correction terms were also developed to bridge the gap between the analytical approximations and the simulation models. The experimental study conducted indicates that the analytical approximations along with the correction terms can serve as a good estimate for the order picking times in a warehouse.

Keywords: queuing networks; parametric decomposition approach; fork and join queues; warehouse order picking.

DOI: 10.1504/IJISE.2019.102468

International Journal of Industrial and Systems Engineering, 2019 Vol.33 No.2, pp.141 - 161

Received: 21 Jun 2017
Accepted: 28 Jan 2018
Published online: 27 Sep 2019 *

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