Queueing analysis for operations modeling in port logistics. Issue 1 (17th November 2019)

• Record Type: Journal Article
• Authors: Legato, Pasquale; Mazza, Rina Mary
• Is Part Of: Maritime business review. Volume 5:Issue 1(2020)
• Page Start: 67
• Page End: 83
• Publication Date: 2019-11-17
• Subjects: Simulation -- Queueing -- Application -- Containers; Shipping -- Periodicals; 387.5
• DOI: 10.1108/MABR-09-2019-0035
• Languages: English
• ISSNs: 2397-3757

Abstract

Abstract : Purpose: The use of queueing network models was stimulated by the appearance (1975) of the exact product form solution of a class of open, closed and mixed queueing networks obeying the local balance principle and solved, a few years later, by the popular mean value analysis algorithm (1980). Since then, research efforts have been produced to approximate solutions for non-exponential services and non-pure random mechanisms in customer processing and routing. The purpose of this paper is to examine the suitability of modeling choices and solution approaches consolidated in other domains with respect to two key logistic processes in container terminals. Design/methodology/approach: In particular, the analytical solution of queueing networks is assessed for the vessel arrival-departure process and the container internal transfer process with respect to a real terminal of pure transshipment. Findings: Numerical experiments show the extent to which a decomposition-based approximation, under fixed or state-dependent arrival rates, may be suitable for the approximate analysis of the queueing network models. Research limitations/implications: The limitation of adopting exponential service time distributions and Poisson flows is highlighted. Practical implications: Comparisons with a simulation-based solution deliver numerical evidence on the companion use of simulation in the daily practice of managing operations in a finite-time horizon under complex policies. Originality/value: Discussion of some open modeling issues and encouraging results provide some guidelines on future research efforts and/or suitable adaption to container terminal logistics of the large body of techniques and algorithms available nowadays for supporting long-run decisions.