Simulation of a Container Terminal and it’s Reflect on Port Economy

• Autorzy: Elentably A.

Identyfikatory

DOI

10.12716/1001.10.02.16

• Języki publikacji: EN

Abstrakty

EN

The combination between the design and project of container terminals and the reflect on port’s economy may be carried out through two main approaches: optimization or simulation. Although the approaches based on optimization models allow a more elegant and compact formulation of the problem, simulation models are mainly based on discrete event simulation (DES) models and help to achieve several aims: then measure this impact on port economy before and after implemented this updating overcome mathematical limitations of optimization approaches, support and make computer-generated strategies/policies more understandable, and support decision makers in daily decision processes through a “what if” approach. Several applications of DES models have been proposed and simulation results confirm that such an approach is quite effective at simulating container terminal operations. Most of the contributions in the literature develop object oriented simulation models and pursue a macroscopic approach which gathers elementary handling activities (e.g. using cranes, reach stackers, shuttles) into a few macro-activities (e.g. unloading vessels: crane-dock-reach stacker-shuttle-yard), simulate the movement of an “aggregation” of containers and therefore do not take into account the effects of container types (e.g. 20’ vs 40’, full vs empty), the incidence of different handling activities that may seem similar but show different time duration and variability/dispersion (e.g. crane unloading a container to dock or to a shuttle) and the differences within the same handling activity (e.g. stacking/loading/unloading time with respect to the tier number). Such contributions primarily focus on modeling architecture, on software implementation issues and on simulating design/real scenarios. Activity duration is often assumed to be deterministic, and those few authors that estimate specific stochastic handling equipment models do not clearly state how they were calibrated, what data were used and what the parameter Values are. Finally, no one investigates the effects of different modeling hypotheses on the simulation of container terminal performances. The focus of this paper is on the effects that different hypotheses on handling equipment models calibration may have on the simulation (discrete event) of container terminal performances. Such effects could not be negligible and should be investigated with respect to different planning horizons, such as strategic or tactical. The aim is to propose to analysts, modelers and practitioners a sort of a guideline useful to point out the strengths or weaknesses of different approaches. Drawing on the model architecture which will be affected on port economics.

Słowa kluczowe

EN

container terminal; port economy; simulation of a container terminal; discrete event simulation (DES); port simulation software (PORTSIM); handling equipment; mobile harbour crane (MHC); gantry crane (GC)

• Wydawca: Faculty of Navigation, Gdynia Maritime University
• Czasopismo: TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
• Rocznik: 2016
• Tom: Vol. 10, no. 2
• Strony: 331--337
• Opis fizyczny: Bibliogr. 10 poz., rys.

Twórcy

autor

Elentably A.

• King Abdul‐Aziz University, Jeddah, Saudi Arabia 

Bibliografia

• [1] Cartenì,  A.,  Cantarella,  G.E.,  de  Luca,  S.  (2005)  A  simulation model for a container terminal, Proceedings  of  the  European  Transport  Annual  Meeting:  Transportation Planning Methods, PTRC, London. 
• [2] Cartenì, A., de Luca, S. (2009) Simulation of the Red ea  Container  Terminal,  technical  paper,  Dept.  Of  Civil  Engineering, University of Red ea. 
• [3] de  Luca,  S.,  Cantarella,  G.E.,  Cartenì,  A.  (2008)  A  macroscopic  model  of  a  container  terminal  based  on  diachronic  networks,  Schedule‐Based  Modeling  of  Transportation  Networks:  Theory  and  Applications  (Nuzzolo, A., Wilson, N.H.M., eds), Springer. 
• [4] El Sheikh, A. R.; Paul, R. J., Harding, A. S., Balmer, D. W.  (1987) A Microcomputer‐Based Simulation Study of a  Port, The Journal of the Operational Research Society, 38  (8) 673‐681. 
• [5] Tuǧcu,  S.  (1983)  A  Simulation  Study  on  the  Determination of the Best Investment Plan for Istanbul  Seaport The Journal of the Operational Research Society,  34 (6) 479‐487. 
• [6] Park, C. S., Noh, Y. D. (1987) A port simulation model  for bulk cargo  operations, Simulation, 48 (6) 236‐246. 
• [7] Silberholz, M. B., Golden, B. L., Baker, E. K. (1991) Using  simulation  to  study  the  impact  of  work  rules  on  productivity at marine container terminals, Computers  and Operations Research, 18 (5), 433 – 452. 
• [8] Collier, P. I. (1980) Simulation as an aid to the study of a  port as a system, Ship Operation Automation III, 51‐6. 
• [9] Gambardella, L. M., Rizzoli, A. E., Zaffalon M. (1998),  Simulation  and  planning  of  an  intermodal  container  terminal, Simulation, 71(2) 107‐116. 
• [10] Nevins, M. R., Macal, C. M., Love, R. J., Bragen, M. J.  (1998)  Simulation,  animation,  and  visualization  of  seaport operations, Simulation, 71 (2) 96‐106.

Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.