A Simulation Based Approach for Efficient Yard Planning in a Container Port
Year 2018,
, 1157 - 1164, 20.09.2018
Murat Çolak
,
Gülşen Aydın Keskin
,
Hatice Esen
,
Canan Bektaş
Abstract
Maritime transport is the most significant one among
several transportation modes. Containers are transported at international level
as a part of maritime transport. Seaports have critical role for efficiency of
container stacking process. It is necessary to complete operations of arriving
vessels at the shortest time in order to provide high customer satisfaction. At
this point, simulation is effectively utilized as a decision support system in
order to improve port processes. In this study, current situation and two
alternative scenarios are compared to each other through simulation so as to
realize the most suitable stack planning by removing bottlenecks in a container
port. It is aimed to determine the most suitable yard layout to provide
minimization of discharging times for arriving vessels, decreasing waiting
times of carriers under quay and yard cranes and fair usage of all equipment.
Thus, it is planned to reduce energy and workforce costs.
References
- [1] Azari, E., Eskandari, H., Nourmohammadi, A. 2017. Decreasing the crane working time in retrieving the containers from a bay. Scientia Iranica, 24(1), 309-318.
- [2] Steenken, D., Voβ, S., Stahlbock, R. 2004. Container terminal operation and operations research – a classification and literature review. OR Spectrum, 26(1), 3-49.
- [3] Branch, A. E. 1986 Elements Of Port Operation And Management, New York, Chapman And Hall Lth.
- [4] Merkuryev, Y., Tolujew, I., Blumel, B., Novitsky, L., Ginters, E. 1998. A Modeling and Simulation Methodology for Managing the Riga Harbour Container Terminal. Simulation, 71(2), 84-95.
- [5] Esmer, S., Tuna, O. 2007. Liman İşletmeciliğinde Bir Karar Destek Sistemi Olarak Simülasyon Yönteminin Analizi. Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 9(4), 120-134.
- [6] Huang, W., Kuo, T., Wu, S. 2007. A Comparison of Analytical Methods and Simulation for Container Terminal Planning. Journal of the Chinese Institute of Industrial Engineers, 24(3), 200-209.
- [7] Lee, D., Wang, H.Q., Miao, L. 2008. Quay crane scheduling with handling priority in port container terminals. Enginering Optimization, 40(2), 179-189.
- [8] Sacone, S., Siri, S. 2009. An integrated simulation-optimization framework for the operational planning of a seaport container terminals. Mathematical and Computer Modelling of Dynamical Systems, 15(3), 275-293.
- [9] Hadjiconstantinou, E., Ma, N.L. 2009. Evaluating straddle carrier deployment policies: a simulation study for the Piraeus container terminal. Maritime Policy & Management, 36(4), 353-366.
- [10] Lee, D., Wang, H.Q. 2010. An approximation algorithm for quay crane scheduling with handling priority in port container terminals. Engineering Optimization, 42(12), 1151-1161.
- [11] Carteni, A., Luca, S. 2012. Tactical and strategic planning for a container terminal: Modelling issues within a discrete event simulation approach. Simulation Modelling Practice and Theory, 21, 123-145.
- [12] Kemme, N. 2012. Effects of storage block layout and automated yard crane systems on the performance of seaport container terminals. OR Spectrum, 34, 563–591.
- [13] Chen, C., Zeng, Q., Zhang, Z. 2012. An Integrating Scheduling Model for Mixed Cross-Operation in Container Terminals. Transport, 27(4), 405-413.
- [14] Esmer, S., Yildiz, G., Tuna, O. 2013. A new simulation modelling approach to continious berth allocation. International Journal of Logistics Research and Applications, 16(5), 398-409.
- [15] Lin, S.W., Ting, C.J. 2014. Solving the dynamic berth allocation problem by simulated annealing. Engineering Optimization, 46(3), 308-327.
- [16] Golias, M., Portal, I., Konur, D., Kaisar, E., Kolomvos, G. 2014. Robust berth scheduling at marine container terminals via hierarchical optimization. Computers & Operations Research, 41, 412–422.
- [17] XiaoLong, H., Gong, X., Jo, J. 2015. A new continuous berth allocation and quay crane assignment model in container terminal. Computers & Industrial Engineering, 89, 15–22.
- [18] Tao, J., Qiu, Y. 2015. A simulation optimization method for vehicles dispatching among multiple container terminals. Expert systems with Applications, 42, 3742-3750.
- [19] He, J. 2016. Berth allocation and quay crane assignment in a container terminal for the trade-off between time-saving and energy-saving. Advanced Engineering Informatics, 30, 390-405.
- [20] Pratap, S., Nayak, A., Kumar, A., Cheikhrouhou, N., Tiwari, M.K. 2017. An integrated decision support system for berth and ship unloader allocation in bulk material handling port. Computers &Industrial Engineering, 106, 386-399.
- [21] Budipriyanto, A., Wirjodirdjo, B., Pujawan, N., Gurning, S. 2017. A simulation study of Collaborative Approach to Berth Allocation Problem under Uncertainty. The Asian Journal of Shipping and Logistics, 33(3), 127-139.
- [22] Stopka, O., Kampf, R. 2018. Determining the most suitable layout of space for the loading units’ handling in the maritime port. Transport, 33(1), 280 – 290.
- [23] Azimi, P., Soofi, P. 2017. An ANN-based optimization model for facility layout problem using simulation technique, Scientia Iranica, 24(1), 364-377.
Bir Konteyner Limanında Etkin Saha Planlaması için Simülasyon Tabanlı Bir Yaklaşım
Year 2018,
, 1157 - 1164, 20.09.2018
Murat Çolak
,
Gülşen Aydın Keskin
,
Hatice Esen
,
Canan Bektaş
Abstract
Deniz
taşımacılığı, çeşitli ulaşım çeşitleri arasında en önemli olanıdır. Konteynerler, deniz taşımacılığının
bir parçası olarak uluslararası düzeyde nakledilmektedir. Limanlar, konteyner istifleme sürecinin verimliliği açısından
kritik bir role sahiptir. Müşteri memnuniyetini en üst düzeyde sağlamak için en
kısa sürede gelen gemilerin operasyonlarını tamamlamak gerekmektedir. Bu
noktada, liman süreçlerini iyileştirmek için simülasyon bir karar destek
sistemi olarak etkin bir şekilde kullanılmaktadır. Bu çalışmada, bir konteyner
limanındaki darboğazları gidererek en uygun istif planlamasını
gerçekleştirebilmek için mevcut durum ve iki alternatif senaryo benzetim
yoluyla birbirleriyle karşılaştırılmıştır. Gelen gemiler için boşaltma
zamanının en aza indirgenmesi, taşıyıcıların vinçlerin altındaki bekleme
sürelerinin kısaltılması ve tüm ekipmanların adil kullanımı için en uygun saha
düzeninin belirlenmesi amaçlanmıştır. Böylece, enerji ve işgücü maliyetlerinin
azaltılması planlanmaktadır.
References
- [1] Azari, E., Eskandari, H., Nourmohammadi, A. 2017. Decreasing the crane working time in retrieving the containers from a bay. Scientia Iranica, 24(1), 309-318.
- [2] Steenken, D., Voβ, S., Stahlbock, R. 2004. Container terminal operation and operations research – a classification and literature review. OR Spectrum, 26(1), 3-49.
- [3] Branch, A. E. 1986 Elements Of Port Operation And Management, New York, Chapman And Hall Lth.
- [4] Merkuryev, Y., Tolujew, I., Blumel, B., Novitsky, L., Ginters, E. 1998. A Modeling and Simulation Methodology for Managing the Riga Harbour Container Terminal. Simulation, 71(2), 84-95.
- [5] Esmer, S., Tuna, O. 2007. Liman İşletmeciliğinde Bir Karar Destek Sistemi Olarak Simülasyon Yönteminin Analizi. Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 9(4), 120-134.
- [6] Huang, W., Kuo, T., Wu, S. 2007. A Comparison of Analytical Methods and Simulation for Container Terminal Planning. Journal of the Chinese Institute of Industrial Engineers, 24(3), 200-209.
- [7] Lee, D., Wang, H.Q., Miao, L. 2008. Quay crane scheduling with handling priority in port container terminals. Enginering Optimization, 40(2), 179-189.
- [8] Sacone, S., Siri, S. 2009. An integrated simulation-optimization framework for the operational planning of a seaport container terminals. Mathematical and Computer Modelling of Dynamical Systems, 15(3), 275-293.
- [9] Hadjiconstantinou, E., Ma, N.L. 2009. Evaluating straddle carrier deployment policies: a simulation study for the Piraeus container terminal. Maritime Policy & Management, 36(4), 353-366.
- [10] Lee, D., Wang, H.Q. 2010. An approximation algorithm for quay crane scheduling with handling priority in port container terminals. Engineering Optimization, 42(12), 1151-1161.
- [11] Carteni, A., Luca, S. 2012. Tactical and strategic planning for a container terminal: Modelling issues within a discrete event simulation approach. Simulation Modelling Practice and Theory, 21, 123-145.
- [12] Kemme, N. 2012. Effects of storage block layout and automated yard crane systems on the performance of seaport container terminals. OR Spectrum, 34, 563–591.
- [13] Chen, C., Zeng, Q., Zhang, Z. 2012. An Integrating Scheduling Model for Mixed Cross-Operation in Container Terminals. Transport, 27(4), 405-413.
- [14] Esmer, S., Yildiz, G., Tuna, O. 2013. A new simulation modelling approach to continious berth allocation. International Journal of Logistics Research and Applications, 16(5), 398-409.
- [15] Lin, S.W., Ting, C.J. 2014. Solving the dynamic berth allocation problem by simulated annealing. Engineering Optimization, 46(3), 308-327.
- [16] Golias, M., Portal, I., Konur, D., Kaisar, E., Kolomvos, G. 2014. Robust berth scheduling at marine container terminals via hierarchical optimization. Computers & Operations Research, 41, 412–422.
- [17] XiaoLong, H., Gong, X., Jo, J. 2015. A new continuous berth allocation and quay crane assignment model in container terminal. Computers & Industrial Engineering, 89, 15–22.
- [18] Tao, J., Qiu, Y. 2015. A simulation optimization method for vehicles dispatching among multiple container terminals. Expert systems with Applications, 42, 3742-3750.
- [19] He, J. 2016. Berth allocation and quay crane assignment in a container terminal for the trade-off between time-saving and energy-saving. Advanced Engineering Informatics, 30, 390-405.
- [20] Pratap, S., Nayak, A., Kumar, A., Cheikhrouhou, N., Tiwari, M.K. 2017. An integrated decision support system for berth and ship unloader allocation in bulk material handling port. Computers &Industrial Engineering, 106, 386-399.
- [21] Budipriyanto, A., Wirjodirdjo, B., Pujawan, N., Gurning, S. 2017. A simulation study of Collaborative Approach to Berth Allocation Problem under Uncertainty. The Asian Journal of Shipping and Logistics, 33(3), 127-139.
- [22] Stopka, O., Kampf, R. 2018. Determining the most suitable layout of space for the loading units’ handling in the maritime port. Transport, 33(1), 280 – 290.
- [23] Azimi, P., Soofi, P. 2017. An ANN-based optimization model for facility layout problem using simulation technique, Scientia Iranica, 24(1), 364-377.