PERT Simülasyon Yöntemiyle Denizyolu Lojistiği İhracat Süreç Analizi

Yıl 2021, , 1053 - 1069, 19.04.2021

Sibel Bayar , Ercan Akan

https://doi.org/10.33206/mjss.819453

Öz

Uluslararası ticaretin en yoğun olarak taşındığı mod olan denizyolu taşımacılığındaki lojistik süreçlerin etkin ve verimli bir biçimde koordine edilmesi, karmaşık bir yapıyı barındırdığından önemli olmaktadır. Bu sürecin iyi yönetilmesi ile aksaksız bir biçimde sürecin işlemesi mümkündür. Bu kapsamda çalışmada ülkelerin ekonomisinde önemli bir rol oynayan ihracat yüklerinin denizyolu taşıma süreci ele alınmıştır. FOB teslim şekli kapsamında ihracatçının sorumluluğu göz önüne alınarak, geminin bordasına kadar olan sürecin analizi yapılmıştır. Bu kapsamda ihracat yükleri için geminin bordasına kadar olan tüm süreçler ortaya konmuş, her bir sürecin olası süreleri belirlenmiş ve PERT Simülasyon kullanılarak toplam süre, kritik faaliyetler ve bolluklar ele alınmıştır. Çalışma FOB teslim şekline uygun olarak tüm denizyolu ihracat süreçlerini ele alması bakımından literatüre katkı sağlamaktadır.

Anahtar Kelimeler

Denizyolu Lojistiği, İhracat Süreci, PERT, Monte Carlo Sİmülasyonu

Process Analysis in Maritime Logistic Export with PERT Simulation

Öz

Effective and efficient coordination of logistics processes in maritime transport, which is the most intensive mode of international trade is crucial as it involves complex structure. A good management of this process results in running the process smoothly. In this context, this study examines the maritime transport process of export cargo, which plays a key role in the economy of the countries. The analysis of the process till the ship board has been made, taking into account the responsibility of the exporter within the scope of FOB delivery method. In this regard, all the processes up to the ship's board for export cargoes were revealed, the possible durations of each process were determined and the total time, critical activities and abundances were discussed applying PERT Simulation.

Anahtar Kelimeler

Maritime Logistics, Export Process, PERT, Monte Carlo Simulation.

Kaynakça

• Aghaie, A., & Mokhtari, H. (2009). Ant colony optimization algorithm for stochastic project crashing problem in PERT networks using MC simulation. The International Journal of Advanced Manufacturing Technology, 45(11-12), 1051.
• Badiru, A. B. (1991). A simulation approach to PERT network analysis. Simulation, 57(4), 245-255.
• Bayar, S. & Ercan, Akan (2020). Bulanık Çevre Ortamında Monte Carlo Simülasyonu ile Denizyolu Lojistiği Fiyatlandırma Süreç Analizi. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, (66), 22-40.
• Bowman, R. A. (1994). Stochastic gradient-based time-cost tradeoffs in PERT networks using simulation. Annals of Operations Research, 53(1), 533-551.
• Branch, A. E. (2006). Export practice and management. Cengage Learning EMEA., London: Thomson Learning
• Brandimarte, P. (2014). Handbook in Monte Carlo simulation: applications in financial engineering, risk management, and economics. John Wiley & Sons.
• Bruzzone, A., Longo, F., Nicoletti, L., Bottani, E., & Montanari, R. (2012). Simulation, analysis and optimization of container terminals processes. International Journal of Modelling, Simulation, and Scientific Computing, 3(04), 1240006.
• Caliskan, A., & Ozturkoglu, Y. (2018). Maritime logistics. In Intelligent Transportation and Planning: Breakthroughs in Research and Practice (pp. 822-845). IGI Global.
• Chávez, J. F., Novelli, A. C., & Leon, M. P. (2020). Export Subsidies in Emerging Markets During the Great Trade Collapse. Economics Bulletin, 40(3), 1879-1892.
• Chen, G., & Yang, Z. (2010). Optimizing time windows for managing export container arrivals at Chinese container terminals. Maritime Economics & Logistics, 12(1), 111-126.
• Cottrell, W. D. (1999). Simplified program evaluation and review technique (PERT). Journal of construction Engineering and Management, 125(1), 16-22.
• Erera, A., Kwek, K. H., Goswami, N., White, C., & Zhang, H. (2003). Comparison of Singapore and USA Sea Cargo Container Export Processes. Report, the Logistics Institute–Asia Pacific, 4.
• Guarnaschelli, A., Bearzotti, L., & Montt, C. (2017). An approach to export process management in a wood product enterprise. International Journal of Production Economics, 190, 88-95.
• Hämäläinen, E., Twrdy, E., & Inkinen, T. (2017). Cost aggregation in export logistics chain. Journal of Open Innovation: Technology, Market, and Complexity, 3(4), 26.
• Hahn, G. J. (1972). Sample sizes for Monte Carlo simulation. I.E.E.E. Trans. Syst. Man Cybern., 2(5), 678-680.
• Jiang, B., Li, J., & Gong, C. (2018). Maritime Shipping and Export Trade on “Maritime Silk Road”. The Asian Journal of Shipping and Logistics, 34(2), 83-90.
• Johnson, N. L., Kotz, S. I., & Balakrishnan, N. (1994). Beta distributions. Continuous univariate distributions. 2nd ed. New York, NY: John Wiley and Sons, 221-235.
• Jouili, T. A. (2019). Impact of seaport infrastructure, logistics performance, and shipping connectivity on merchandise exports. International Journal of Computer Science and Network Security, 19(5), 259-264.
• Kang, J., Ryu, K. R., & Kim, K. H. (2006). Deriving stacking strategies for export containers with uncertain weight information. Journal of Intelligent Manufacturing, 17(4), 399-410.
• Karabulut, M. (2017). Application of Monte Carlo simulation and PERT/CPM techniques in planning of construction projects: A Case Study. Periodicals of Engineering and Natural Sciences, 5(3).
• Kim, K. H., Park, Y. M., & Ryu, K. R. (2000). Deriving decision rules to locate export containers in container yards. European Journal of Operational Research, 124(1), 89-101.
• Lee, Y., & Chao, S. L. (2009). A neighbourhood search heuristic for pre-marshalling export containers. European Journal of Operational Research, 196(2), 468-475.
• Lee, E. S., & Song, D. W. (2010). Knowledge management for maritime logistics value: discussing conceptual issues. Marit. Pol. Mgmt., 37(6), 563-583.
• Malcolm, D. G., Roseboom, J. H., Clark, C. E., & Fazar, W. (1959). Application of a technique for research and development program evaluation. Operations research, 7(5), 646-669.
• Manova, K., & Zhang, Z. (2012). Export prices across firms and destinations. The Quarterly Journal of Economics, 127(1), 379-436.
• Nam, H. S., & Song, D. W. (2011). Defining maritime logistics hub and its implication for container port. Maritime Policy & Management, 38(3), 269-292.
• Pérez-Mesa, J. C., Galdeano-Gómez, E., & Andújar, J. A. S. (2012). Logistics network and externalities for short sea transport: An analysis of horticultural exports from southeast Spain. Transport Policy, 24, 188-198.
• Piltz, B. (2020). Incoterms® 2020. Revija Kopaoničke škole prirodnog prava, 2(1), 9-28.
• Pontrandolfo, P. (2000). Project duration in stochastic networks by the PERT-path technique. International Journal of Project Management, 18(3), 215-222.
• Rahardianto, R., Sarno, R., & Budiawati, G. I. (2018, September). Performance Time Evaluation of Domestic Container Terminal Using Process Mining and PERT. In 2018 International Seminar on Application for Technology of Information and Communication (pp. 469-475). IEEE.
• Tahar, R. M., & Hussain, K. (2000). Simulation and analysis for the Kelang Container Terminal operations. Logistics information management.
• T.C. Ticaret Bakanlığı. (2020). Taşıma şekillerine göre dış ticaret, https://ticaret.gov.tr/data/5d63d89d13b8762f7c43a738/16-Tasima%20Sekillerine%20Gore%20Dis%20Ticaret.pdf Ziyaret Tarihi: 25.10.2020
• Tenjo-García, J. S., & Figueroa-García, J. C. (2019, June). Simulation-based fuzzy PERT problems. In 2019 IEEE Colombian Conference on Applications in Computational Intelligence (ColCACI) (pp. 1-5). IEEE.
• Tongzon, J. L. (1989). The impact of wharfage costs on Victoria’s export-oriented industries. Maritime Studies, 1989(46), 14-19.
• Ueberhuber, C. W. (1997). Monte Carlo techniques. Numerical Computation 2: Methods, Software, and Analysis. Berlin: Springer Science Business Media.
• Uddin, K. S., & Jinia, A. A. (2017). Simulation of Automated Warehouse System: Using CPM and PERT Method. Simulation, 9(11).
• UNCTAD. (2020). Review of Maritime Transport 2019, United Nations Conference on Trade and Development, New York: United Nations Publications.
• Utikad. (2020). Incoterms 2020, https://www.utikad.org.tr/Images/Duyuru/08012020incoterms2020414196.pdf , Ziyaret Tarihi: 17.10. 2020.
• Vose, D. (2008). Risk analysis: a quantitative guide. John Wiley & Sons.