Statistical analysis for modeling ship operation processes in ports

• Autorzy: Özkan Emin Deniz , Koçer Umay Uzunoğlu , Nas Selçuk

Identyfikatory

DOI

10.17402/421

• Języki publikacji: EN

Abstrakty

EN

The proper selection of statistical distributions is important for modeling port operations using simulations or queuing theory. The aim of this study was to determine the appropriate statistical distributions for modeling random processes related to ship operations in ports, including ship arrivals, berthing maneuver processes, service processes, and unberthing maneuver processes. A literature review was performed on the statistical distributions used in these random processes. In addition, the port data on ship operations gathered from three different ports in Turkey were examined. Goodness of fit tests were conducted to determine the appropriate distribution for each process.

Słowa kluczowe

EN

port; ship; ship operations; statistical distributions; goodness of fit; modeling

• Wydawca: Wydawnictwo Naukowe Akademii Morskiej w Szczecinie
• Czasopismo: Zeszyty Naukowe Akademii Morskiej w Szczecinie
• Rocznik: 2020
• Tom: nr 62 (134)
• Strony: 71--79
• Opis fizyczny: Bibliogr. 23 poz., rys., tab.

Twórcy

autor

Özkan Emin Deniz

• Dokuz Eylül University

autor

Koçer Umay Uzunoğlu

• Dokuz Eylül University

autor

Nas Selçuk

• Dokuz Eylül University

Bibliografia

• 1. Agerschou, H. (2004) Facilities Requirements. In: Agerschou, H. (ed.) Planning and Design of Ports and Marine Terminals (pp. 5–20). 2nd Edition. London: Thomas Telford.
• 2. Bugaric, U. & Petrovic, D. (2007) Increasing the Capacity of Terminal for Bulk Cargo Unloading. Simulation Modelling Practice and Theory 15(10), pp. 1366–1381.
• 3. Demirci, E. (2003) Simulation Modelling and Analysis of a Port Investment. Simulation 79(2), pp. 94–105.
• 4. Dragovic, B., Park, N.K. & Radmilovic, Z. (2006) ShipBerth Link Performance Evaluation: Simulation and Analytical Approaches. Maritime Policy & Management 33(3), pp. 281–299.
• 5. Esmer, S., Yildiz, G. & Tuna, O. (2013) A New Simulation Modelling Approach to Continuous Berth Allocation. International Journal of Logistics Research and Applications 16(5), pp. 398–409.
• 6. Groenveld, R. & Wanders, S. (1999) Computer simulation model international container terminal Tanjung Perak, Surabaya, Indonesia. The International Workshop on Harbour, Maritime & Industrial Logistics Modelling and Simulation (HMS 1999), 16–18 September 1999, Genoa, Italy.
• 7. Huang, S.Y., Hsu, W.J., Chen, C., Ye, R. & Nautiyal, S. (2008) Capacity Analysis of Container Terminals Using Simulation Techniques. International Journal of Computer Applications in Technology 32(4), pp. 246–253.
• 8. Imai, A., Sun, X., Nishimura, E. & Papadimitriou, S. (2005) Berth Allocation in a Container Port: Using a Continuous Location Space Approach. Transportation Research Part B 39(3), pp. 199–221.
• 9. Kia, M., Shayan, E. & Ghotb, F. (2002) Investigation of Port Capacity Under A New Approach by Computer Simulation. Computers & Industrial Engineering 42(2–4), pp. 533–540.
• 10. Kuo, T.C., Huang, W.C., Wu, S.C. & Cheng, P.L. (2006) A Case Study of Inter-Arrival Time Distributions of Container Ships. Journal of Marine Science and Technology 14(3), pp. 155–164.
• 11. Lai, K.K. & Shih, K. (1992) A Study of Container Berth Allocation. Journal of Advanced Transportation 26(1), pp. 45–60.
• 12. Layaa, J. & Dullaert, W. (2014) Measuring and Analysing Terminal Capacity in East Africa: The Case of the Seaport of Dar es Salaam. Maritime Economics & Logistics 16(2), pp. 141–164.
• 13. Lee, T.W., Park, N.K. & Lee, D.W. (2003) A Simulation Study for the Logistics Planning of A Container Terminal in view of SCM. Maritime Policy & Management 30(3), pp. 243–254.
• 14. Lin, J., Gao, B. & Zhang, C. (2014) Simulation-based Investment Planning for Humen Port. Simulation Modelling Practice and Theory 40, pp. 161–175.
• 15. Nas, S. (2013) Teknik Seyir Hizmetlerinde Kaynakların Simülasyon Modellemesi Yöntemiyle Optimizasyonu: Römorkör Park Yeri Seçimi. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi 5(2), pp. 57–81.
• 16. Nas, S., Özkan, E.D. & Uçan, E. (2016) Römorkörcülük Hizmeti Yetki Sahalarında Römorkör Sayısının Simülasyon Modellemesi Yöntemiyle Tespiti. Journal of ETA Maritime Science 4(1), pp. 91–99.
• 17. Olba, X.B., Daamen, W., Vellinga, T. & Hoogendoorn, S.P. (2018) State-of-the-art of Port Simulation Models for Risk and Capacity Assessment based on the Vessel Navigational Behaviour Through the Nautical Infrastructure. Journal of Traffic and Transportation Engineering (English Edition) 5(5), pp. 335–347.
• 18. Ports regulation (2012) Official Gazette of the Republic of Turkey. Number: 28453, Date: 31.10.2012.
• 19. Shabayek, A.A. & Yeung, W.W. (2001) Effect of Seasonal Factors on Performance of Container Terminals. Journal of Waterway, Port, Coastal, and Ocean Engineering 127(3), pp. 135–140.
• 20. Tang, G., Guo, Z., Yu, X., Song, X. & Du, P. (2014) SPAC to Improve Port Performance for Seaports with Very Long One-Way Entrance Channels. Journal of Waterway, Port, Coastal, and Ocean Engineering 140(4), 04014011.
• 21. Tang, G., Wang, W., Song, X., Guo, Z., Yu, X. & Qiao, F. (2016) Effect of Entrance Channel Dimensions on Berth Occupancy of Container Terminals. Ocean Engineering 117, pp. 174–187.
• 22. Uğurlu, Ö., Yüksekyildiz, E. & Köse, E. (2014) Simulation Model on Determining of Port Capacity and Queue Size: A Case Study for BOTAS Ceyhan Marine Terminal. The International Journal on Marine Navigation and Safety of Sea Transportation 8(1), pp. 143–150.
• 23. Zhou, P.-F., Guo, Z.-J. & Song, X.-Q. (2006) Simulation Study on Container Terminal Performance. Proceedings of 2006 International Conference on Management Science & Engineering ICMSE’06 (13th), 5–7 October 2006, Lille, France.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).