Modeling landside container terminal queues: Exact analysis and approximations

Roy, Debjit; Ommeren, Jan-Kees van; Koster, René de; Gharehgozli, Amir

doi:10.1016/j.trb.2022.05.012

Cited by 14 publications

(2 citation statements)

References 72 publications

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“…Among these, queueing-focused literature has often delivered analytical models that, if well tuned, can be pursued to produce an exact or, in most cases, a good approximation of the metrics of the terminal's (sub)system for a variety of sets of input parameters. To name a few, a semi-open queueing network model with bulk arrivals (by train), shared stack crane resources and multiclass containers is used in the study by Roy et al (2022) to analyze the impact of prioritizing in stacking and internal transport handling the containers delivered by train. A closed-queueing network is proposed in the study by Xiang et al (2022) to estimate the performance of an automated container terminal under traffic congestion, unbalanced task assignment, container batch arrival and different berth and yard layouts.…”

Section: Literature Reviewmentioning

confidence: 99%

Queueing networks for supporting container storage and retrieval

Legato

Mazza

2023

MABR

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PurposeAn integrated queueing network focused on container storage/retrieval operations occurring on the yard of a transshipment hub is proposed. The purpose of the network is to support decisions related to the organization of the yard area, while also accounting for operations policies and times on the quay.Design/methodology/approachA discrete-event simulation model is used to reproduce container handling on both the quay and yard areas, along with the transfer operations between the two. The resulting times, properly estimated by the simulation output, are fed to a simpler queueing network amenable to solution via algorithms based on mean value analysis (MVA) for product-form networks.FindingsNumerical results justify the proposed approach for getting a fast, yet accurate analytical solution that allows carrying out performance evaluation with respect to both organizational policies and operations management on the yard area.Practical implicationsPractically, the expected performance measures on the yard subsystem can be obtained avoiding additional time-expensive simulation experiments on the entire detailed model.Originality/valueAs a major takeaway, deepening the MVA for generally distributed service times has proven to produce reliable estimations on expected values for both user- and system-oriented performance metrics.

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Section: Literature Reviewmentioning

confidence: 99%

Queueing networks for supporting container storage and retrieval

Legato

Mazza

2023

MABR

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“…In project management and supply chain management, the split-join structure is typically used for representing the arrival of an order composed of several different items or products from a vendor, or for synchronization between arriving and departing vehicles at the transshipment location [12,13]. The split-join structure is also prevalent in healthcare and, in particular, in emergency departments, where multiple customer classes share multiple processing resources [14,15], in supply chain networks of high-tech manufacturers with multiple suppliers that each produce a unique component of the product [16][17][18][19], and in ocean transport for managing container terminals [20].…”

Section: Introductionmentioning

confidence: 99%

The Delay Time Profile of Multistage Networks with Synchronization

Barron

2023

Mathematics

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The interaction between projects and servers has grown significantly in complexity; thus, applying parallel calculations increases dramatically. However, it should not be ignored that parallel processing gives rise to synchronization constraints and delays, generating penalty costs that may overshadow the savings obtained from parallel processing. Motivated by this trade-off, this study investigates two special and symmetric systems of split–join structures: (i) parallel structure and (ii) serial structure. In a parallel structure, the project arrives, splits into m parallel groups (subprojects), each comprising n subsequent stages, and ends after all groups are completed. In the serial structure, the project requires synchronization after each stage. Employing a numerical study, we investigates the time profile of the project by focusing on two types of delays: delay due to synchronization overhead (occurring due to the parallel structure), and delay due to overloaded servers (occurring due to the serial structure). In particular, the author studies the effect of the number of stages, the number of groups, and the utilization of the servers on the time profile and performance of the system. Further, this study shows the efficiency of lower and upper bounds for the mean sojourn time. The results show that the added time grows logarithmically with m (parallelism) and linearly with n (seriality) in both structures. However, comparing the two types of split–join structures shows that the synchronization overhead grows logarithmically undr both parallelism and seriality; this yields an unexpected duality property of the added time to the serial system.

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