A queuing network model of the logistic activities related to the arrival, berthing, and departure processes of vessels at a container terminal is presented in this paper. Non-standard service stations, time-dependent priority mechanisms, and complex resource allocation policies prevent the use of analytical approaches to the solution. By adopting the process approach, a simulation model for the above queuing network has been developed. This requires a limited effort when using graphical objects of the Visual SLAM language for discrete-event simulation. Good validation results, against response measures on a real system, are obtained using aggregated data related to a finite time horizon. Steady-state simulation results illustrate the use of the model for a "what if" optimisation approach to the berth planning problem. © 2001 Elsevier Science B.V.

Berth planning and resources optimisation at a container terminal via discrete event simulation

LEGATO Pasquale;MAZZA Rina Mary
2001-01-01

Abstract

A queuing network model of the logistic activities related to the arrival, berthing, and departure processes of vessels at a container terminal is presented in this paper. Non-standard service stations, time-dependent priority mechanisms, and complex resource allocation policies prevent the use of analytical approaches to the solution. By adopting the process approach, a simulation model for the above queuing network has been developed. This requires a limited effort when using graphical objects of the Visual SLAM language for discrete-event simulation. Good validation results, against response measures on a real system, are obtained using aggregated data related to a finite time horizon. Steady-state simulation results illustrate the use of the model for a "what if" optimisation approach to the berth planning problem. © 2001 Elsevier Science B.V.
2001
Logistics; Performance optimisation; Queuing; Simulation; Information Systems and Management; Management Science and Operations Research; Statistics, Probability and Uncertainty; Applied Mathematics; Modeling and Simulation; Transportation
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/269434
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