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Vessels Arrival Process and its Application to the SHIP/M/ $$\infty$$ ∞ Queue

Author

Listed:
  • Antonio Di Crescenzo

    (Università degli Studi di Salerno)

  • Barbara Martinucci

    (Università degli Studi di Salerno)

  • Paola Paraggio

    (Università degli Studi di Salerno)

Abstract

In modeling of port dynamics it seems reasonable to assume that the ships arrive on a somewhat scheduled basis and that there is a constant lay period during which, in a uniform way, each vessel can arrive at the port. In the present paper, we study the counting process N(t) which represents the number of scheduled vessels arriving during the time interval (0, t], $$t>0$$ t > 0 . Specifically, we provide the explicit expressions of the probability generating function, the probability distribution and the expected value of N(t). In some cases of interest, we also obtain the probability law of the stationary counting process representing the number of arrivals in a time interval of length t when the initial time is an arbitrarily chosen instant. This leads to various results concerning the autocorrelations of the random variables $$X_i$$ X i , $$i\in \mathbb {Z}$$ i ∈ Z , which give the actual interarrival time between the $$(i-1)$$ ( i - 1 ) -th and the i-th vessel arrival. Finally, we provide an application to a stochastic model for the queueing behavior at the port, given by a queueing system characterized by stationary interarrival times $$X_i$$ X i , exponential service times and an infinite number of servers. In this case, some results on the average number of customers and on the probability of an empty queue are disclosed.

Suggested Citation

  • Antonio Di Crescenzo & Barbara Martinucci & Paola Paraggio, 2023. "Vessels Arrival Process and its Application to the SHIP/M/ $$\infty$$ ∞ Queue," Methodology and Computing in Applied Probability, Springer, vol. 25(1), pages 1-33, March.
  • Handle: RePEc:spr:metcap:v:25:y:2023:i:1:d:10.1007_s11009-023-10003-8
    DOI: 10.1007/s11009-023-10003-8
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    References listed on IDEAS

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    1. Shaul K. Bar-Lev & Hans Blanc & Onno Boxma & Guido Janssen & David Perry, 2013. "Tandem Queues with Impatient Customers for Blood Screening Procedures," Methodology and Computing in Applied Probability, Springer, vol. 15(2), pages 423-451, June.
    2. Tayfur Altiok, 2000. "Tandem queues in bulk port operations," Annals of Operations Research, Springer, vol. 93(1), pages 1-14, January.
    3. Carlo Lancia & Gianluca Guadagni & Sokol Ndreca & Benedetto Scoppola, 2018. "Asymptotics for the late arrivals problem," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 88(3), pages 475-493, December.
    4. Dimitrakopoulos, Yiannis & Economou, Antonis & Leonardos, Stefanos, 2021. "Strategic customer behavior in a queueing system with alternating information structure," European Journal of Operational Research, Elsevier, vol. 291(3), pages 1024-1040.
    5. van Asperen, E. & Dekker, R. & Polman, M. & de Swaan Arons, H. & Waltman, L., 2003. "Arrival Processes for Vessels in a Port Simulation," ERIM Report Series Research in Management ERS-2003-067-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    6. G. Guadagni & S. Ndreca & B. Scoppola, 2011. "Queueing systems with pre-scheduled random arrivals," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 73(1), pages 1-18, February.
    7. Goerlandt, Floris & Kujala, Pentti, 2011. "Traffic simulation based ship collision probability modeling," Reliability Engineering and System Safety, Elsevier, vol. 96(1), pages 91-107.
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