Open Access
2017 Comparing an Approximate Queuing Approach with Simulation for the Solution of a Cross-Docking Problem
Roberta Briesemeister, Antônio G. N. Novaes
J. Appl. Math. 2017: 1-11 (2017). DOI: 10.1155/2017/4987127

Abstract

Cross-docking is a logistics management concept in which products are temporarily unloaded at intermediate facilities and loaded onto output trucks to be sent to their final destination. In this paper, we propose an approximate nonstationary queuing model to size the number of docks to receive the trucks, so that their unloading will be as short as possible at the receiving dock, thus making the cross-docking process more efficient. It is observed that the stochastic queuing process may not reach the steady equilibrium state. A type of modeling that does not depend on the stationary characteristics of the process developed is applied. In order to measure the efficiency, performance, and possible adjustments of the parameters of the algorithm, an alternative simulation model is proposed using the Arena® software. The simulation uses analytic tools to make the problem more detailed, which is not allowed in the theoretical model. The computational analysis compares the results of the simulated model with the ones obtained with the theoretical algorithm, considering the queue length and the average waiting time of the trucks. Based on the results obtained, the simulation represented very well the proposed problem and possible changes can be easily detected with small adjustments in the simulated model.

Citation

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Roberta Briesemeister. Antônio G. N. Novaes. "Comparing an Approximate Queuing Approach with Simulation for the Solution of a Cross-Docking Problem." J. Appl. Math. 2017 1 - 11, 2017. https://doi.org/10.1155/2017/4987127

Information

Received: 24 February 2017; Revised: 6 April 2017; Accepted: 4 May 2017; Published: 2017
First available in Project Euclid: 16 June 2017

zbMATH: 07037479
MathSciNet: MR3661584
Digital Object Identifier: 10.1155/2017/4987127

Rights: Copyright © 2017 Hindawi

Vol.2017 • 2017
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