Araştırma Makalesi
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DENİZ ULAŞTIRMASINDA ETMEN TABANLI MODELLEME VE BENZETİM İNCELEMESİ

Yıl 2019, , 151 - 176, 16.12.2019
https://doi.org/10.18613/deudfd.659801

Öz

Deniz yoluyla ulaşımı, yük ve yolcu taşımacılığında, son yıllarda değişimler yaşanmaktadır. Deniz taşımacılığındaki önemli konular; güvenlik, deniz ortamının korunması, optimal zaman ve minimum maliyet ile bir denge noktası yakalanmasıdır. Simülasyon, kazaların önlenmesi ve güvenlik zayıflıklarının tespiti gibi problem çözme için etkili yöntemlerden biridir. Benzetimler ayrıca mevcut durumların analizi, tasarım veya modellerin test edilmesi için de yaygın şekilde kullanılmaktadır. Benzetim çalışmaları temel olarak Kesikli Olay (Discrete Event) Benzetim, Sistem Dinamikleri (System Dynamics) yaklaşımları ve Etmen Tabanlı (Agent-based) Modelleme ve Benzetim yaklaşımı olarak yazında yer almaktadır. Bunlardan Etmen tabanlı benzetim modelleri, belirli tanımlanmış kuralları uygulayan etmenlerin birbirleriyle ve çevreleriyle olan ilişkilerinden oluşur. Yöntem; fizik, biyoloji, sosyal bilimler, mühendislik ve yönetim bilimlerini kapsayan çok çeşitli disiplinlerde kullanılmaktadır. Deniz ulaştırmasına yönelik etmen tabanlı modelleme/benzetim çalışmalarının tespit edilmesi bu çalışmanın amacını oluşturmaktadır. Bu amaçla özellikle deniz ulaştırmasında kullanılan etmen tabanlı modelleme ve benzetim modelleme çalışmalarına odaklanılmış, çalışılan konu ve içeriklerin ortaya çıkarılması hedeflenmiştir. Gerçekleştirilen yazın taramasının sonucunda deniz ulaştırmasına yönelik modelleme/benzetim çalışmalarının çoğunlukla deniz trafiğinin analizi, deniz haydutluğu ve güvenlik, liman ekipmanlarının verimliliği, arama kurtarma operasyonları başlıklarında yoğunlaştığı tespit edilmiştir.

Kaynakça

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  • Allan, R. (2010). Survey of agent based modelling and simulation tools. Warrington: 2010 Science and Technology Facilities Council. DOI: 10.1007/978-0-85729-139-4.
  • Allen, T. (2011). Introduction to discrete event simulation and agent-based modeling voting systems, health care, military, and manufacturing. Springer-Verlag London Limited 2011.
  • Altiok, T. ve Melamed, B. (2007). Simulation modeling and analysis with ARENA, Amsterdam: Elsevier Academic Press.
  • Bas G., De Boo K., Vaes-Van de Hulsbeek A.M. ve Nikolic I. (2007). MarPEM: An agent based model to explore the effects of policy instruments on the transition of the maritime fuel system away from HFO. Transportation Research Part D. 55:162–174. DOI: 10.1016/j.trd.2017.06.017.
  • Baber, C., Stanton, N.A., Atkinson, J. McMaster, R. ve Houghton, R.J. (2013). Using social network analysis and agent-based modelling to explore information flow using common operational pictures for maritime search and rescue operations, Ergonomics, 56(6): 889-905. DOI: 10.1080/00140139.2013.788216.
  • Cheng, T-T., Qing W. ve Feng M. (2017). An artificial potential field-based simulation approach for maritime traffic flow. Proceedings of 4th International Conference on Transportation Information Safety (ICTIS). City of Edmonton, Canada.
  • Chion, C. (2011). An agent-based model for the sustainable management of navigation activities in the saint lawrence estuary (Order No. NR78333). Doktora Tezi, Ecole de technologıe supérıeure, Montreal. Available from ProQuest Dissertations ve Theses Global. (930932188).
  • Dağkıran, B. (2018). Etmen Tabanlı Modelleme ve Simülasyon Yaklaşımı İle Gemi Trafik Hizmetleri Sosyo Teknik Sisteminin Analizi. Yüksek Lisans Tezi, İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, İstanbul.
  • Decraene, J., Zeng, F., Low, M.Y.H., Cai, W., Cheng, Y.Y. ve Choo, C.S.. (2012). Evolutionary design of experiments using the mapreduce framework. In Proceedings of the 2011 Summer Computer Simulation Conference (SCSC '11). CA. USA.
  • Douma, A. M., J. Van Hillegersberg, and P. C. Schuur. 2012. Design and Evaluation of a Simulation Game to Introduce a Multi-Agent System for Barge Handling in a Seaport. Decision Support Systems 53:465–472. DOI: 10.1016/j.dss.2012.02.013.
  • Falkingham,L.T. ve Reeves,R. (1998). A technique for analysing research in a field, applied to literature on the Management of R&D at the section level. Scientometrics, 42(2): 97-120.
  • Farias, Monteiro de ve Leite,L. T. (2006). Simulation and Control of Maritime Area through Multi-Agent Systems and Geographical Information Systems, in Proceedings of International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC'06), Vienna, 2005, pp.734-738. doi: 10.1109/CIMCA.2005.1631351.
  • Fang, Z., Qi, Y., Hao, J., Huang, J., ve Dong, M. (2014). Agent-Based Simulation Analysis on the Effect of an LNG Terminal on a Port Transport System. In: Proceedings of 14th COTA International Conference of Transportation Professionals. Changsha, China.
  • Fish, J.M. (2017). A cross-disciplinary approach to the maritime security risk of piracy and lessons learned from agent-based modeling. Doctor of Philosophy, Old Dominion University, International Studies. USA- Virginia. DOI: 10.25777/spk1-5d03.
  • Garro, A., Monaco, M.F., Russo,W., Sammarra,M. ve Sorrentino,G. (2015). Agent-based simulation for the evaluation of a new dispatching model for the straddle carrier pooling problem. Journal Simulation, 91 (2), 181-202. DOI: 10.1177/0037549714566699.
  • Hansen, F.T., Potthoff , M., Uhrenholdt, T., Vo, H.D., Linden, O. ve Andersen, J.H. (2015). Development of a prototype tool for ballast water risk management using a combination of hydrodynamic models and agent-based modeling. The WMU Journal of Maritime Affairs (JoMA) (2015) 14: 219–245. DOI: 10.1007/s13437-014-0067-8.
  • Harris, S.P., Dixon, D.S., Dunn, D.L. ve Romich, A.N. (2012). Simulation modeling for maritime port security. Journal of Defense Modeling and Simulation: Applications, Methodology, Technology,10 (2), 193–201. DOI: 10.1177/1548512917751964.
  • Henesey, L., Davidsson, P. ve Persson, J.A. Evaluation of Automated Guided Vehicle Systems for Container Terminals Using Multi Agent Based Simulation. In: Proceedings of MABS 2008: Multi-agent-based simulation IX. Budapest, Hungary. DOI: 10.1007/978-3-642-01991-3_7.
  • Hrstka O, Vaňek O, Kopřiva Š, Jiří, Z., Jan, F. ve Pěchouček M. (2015). Agent-based approach to illegal maritime behavior modeling Scientific Journals of the Maritime University of Szczecin. 2015, 42 (114): 101-111. DOI: 10.17402/026.
  • Huet T., Osman T, ve Ray C. (2003). Modelling Traffic Navigation Network With A Multi-Agent Platform.In: Proceedings of 17th European Simulation Multiconference. Nottingham, United Kingdom.
  • Jakob, M., Vanek,O., Urban, S., Benda, P. ve Pechoucek, M. (2010). AgentC: Agent-based Testbed for Adversarial Modeling and Reasoning in the Maritime Domain. In: Proc. of 9th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2010). Toronto, Canada.
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  • Ni, B., Li, Z., Zhang, P. ve Li, X. (2017). An evacuation model for passenger ships that includes the influence of obstacles in cabins. Hindawi Mathematical Problems in Engineering, Volume 2017, 1-21. DOI: 10.1155/2017/5907876.
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  • Öztanrıseven, F. (2016). Modeling economic impacts of the inland waterway transportation system. Doktora Tezi. University of Arkansas, Industrial Engineering, Arkansas.
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  • İnternet Kaynakları
  • Macal, C.M. ve North, M.J. 2006. Introduction to agent-based modeling and Simulation. MCS LANS Informal Seminar November 29, 2006. https://www.mcs.anl.gov/~leyffer/listn/slides-06/MacalNorth.pdf, Erişim Tarihi: 04.02.2019.
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A REVIEW OF AGENT BASED SIMULATION AND MODELING IN MARITIME TRANPORTATION

Yıl 2019, , 151 - 176, 16.12.2019
https://doi.org/10.18613/deudfd.659801

Öz

Maritime transportation, cargo and passenger transportation have been changing in recent years. Important issues in maritime transport are mainly: safety, security, protection of the marine environment, capture a balance point by optimal timing and minimum costs. Simulation is one of the effective methods for problem solving such as prevention of accidents and detection of security weaknesses. Simulations are also widely used to analyze existing conditions, to understand behavior, to design, to evaluate system through models. The simulation studies take place in the literature as Discrete Event Simulation, System Dynamics and Agent-based Modeling and Simulation. Agent-based Simulation models consist of the agents that implement defined rules, agent-agent relationships and interactions between agent and its environment. Agent-based Simulation is used in a wide variety of disciplines including physics, biology, social sciences, engineering and management sciences. The aim of this study is to determine the simulation studies especially for the agent-based models in maritime transportation. For this purpose, the simulation/modeling studies used in maritime transportation have been reviewed and the subjects and contents that are focused on the agent-based models have been revealed. As a result of the literature review, it has been determined that the modeling/ simulation studies for maritime transportation are mostly concentrated in the analysis of maritime traffic, piracy and maritime security, efficiency of port equipment and search and rescue operations.

Kaynakça

  • Abar, S., Theodoropoulos G., Lemarinier P. ve Hare G.M.P (2017). Agent based modelling and simulation tools: A review of the state-of-art software. Computer Science Review, 24:13–33. DOI:10.1016/j.cosrev.2017.03.001.
  • Allan, R. (2010). Survey of agent based modelling and simulation tools. Warrington: 2010 Science and Technology Facilities Council. DOI: 10.1007/978-0-85729-139-4.
  • Allen, T. (2011). Introduction to discrete event simulation and agent-based modeling voting systems, health care, military, and manufacturing. Springer-Verlag London Limited 2011.
  • Altiok, T. ve Melamed, B. (2007). Simulation modeling and analysis with ARENA, Amsterdam: Elsevier Academic Press.
  • Bas G., De Boo K., Vaes-Van de Hulsbeek A.M. ve Nikolic I. (2007). MarPEM: An agent based model to explore the effects of policy instruments on the transition of the maritime fuel system away from HFO. Transportation Research Part D. 55:162–174. DOI: 10.1016/j.trd.2017.06.017.
  • Baber, C., Stanton, N.A., Atkinson, J. McMaster, R. ve Houghton, R.J. (2013). Using social network analysis and agent-based modelling to explore information flow using common operational pictures for maritime search and rescue operations, Ergonomics, 56(6): 889-905. DOI: 10.1080/00140139.2013.788216.
  • Cheng, T-T., Qing W. ve Feng M. (2017). An artificial potential field-based simulation approach for maritime traffic flow. Proceedings of 4th International Conference on Transportation Information Safety (ICTIS). City of Edmonton, Canada.
  • Chion, C. (2011). An agent-based model for the sustainable management of navigation activities in the saint lawrence estuary (Order No. NR78333). Doktora Tezi, Ecole de technologıe supérıeure, Montreal. Available from ProQuest Dissertations ve Theses Global. (930932188).
  • Dağkıran, B. (2018). Etmen Tabanlı Modelleme ve Simülasyon Yaklaşımı İle Gemi Trafik Hizmetleri Sosyo Teknik Sisteminin Analizi. Yüksek Lisans Tezi, İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, İstanbul.
  • Decraene, J., Zeng, F., Low, M.Y.H., Cai, W., Cheng, Y.Y. ve Choo, C.S.. (2012). Evolutionary design of experiments using the mapreduce framework. In Proceedings of the 2011 Summer Computer Simulation Conference (SCSC '11). CA. USA.
  • Douma, A. M., J. Van Hillegersberg, and P. C. Schuur. 2012. Design and Evaluation of a Simulation Game to Introduce a Multi-Agent System for Barge Handling in a Seaport. Decision Support Systems 53:465–472. DOI: 10.1016/j.dss.2012.02.013.
  • Falkingham,L.T. ve Reeves,R. (1998). A technique for analysing research in a field, applied to literature on the Management of R&D at the section level. Scientometrics, 42(2): 97-120.
  • Farias, Monteiro de ve Leite,L. T. (2006). Simulation and Control of Maritime Area through Multi-Agent Systems and Geographical Information Systems, in Proceedings of International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC'06), Vienna, 2005, pp.734-738. doi: 10.1109/CIMCA.2005.1631351.
  • Fang, Z., Qi, Y., Hao, J., Huang, J., ve Dong, M. (2014). Agent-Based Simulation Analysis on the Effect of an LNG Terminal on a Port Transport System. In: Proceedings of 14th COTA International Conference of Transportation Professionals. Changsha, China.
  • Fish, J.M. (2017). A cross-disciplinary approach to the maritime security risk of piracy and lessons learned from agent-based modeling. Doctor of Philosophy, Old Dominion University, International Studies. USA- Virginia. DOI: 10.25777/spk1-5d03.
  • Garro, A., Monaco, M.F., Russo,W., Sammarra,M. ve Sorrentino,G. (2015). Agent-based simulation for the evaluation of a new dispatching model for the straddle carrier pooling problem. Journal Simulation, 91 (2), 181-202. DOI: 10.1177/0037549714566699.
  • Hansen, F.T., Potthoff , M., Uhrenholdt, T., Vo, H.D., Linden, O. ve Andersen, J.H. (2015). Development of a prototype tool for ballast water risk management using a combination of hydrodynamic models and agent-based modeling. The WMU Journal of Maritime Affairs (JoMA) (2015) 14: 219–245. DOI: 10.1007/s13437-014-0067-8.
  • Harris, S.P., Dixon, D.S., Dunn, D.L. ve Romich, A.N. (2012). Simulation modeling for maritime port security. Journal of Defense Modeling and Simulation: Applications, Methodology, Technology,10 (2), 193–201. DOI: 10.1177/1548512917751964.
  • Henesey, L., Davidsson, P. ve Persson, J.A. Evaluation of Automated Guided Vehicle Systems for Container Terminals Using Multi Agent Based Simulation. In: Proceedings of MABS 2008: Multi-agent-based simulation IX. Budapest, Hungary. DOI: 10.1007/978-3-642-01991-3_7.
  • Hrstka O, Vaňek O, Kopřiva Š, Jiří, Z., Jan, F. ve Pěchouček M. (2015). Agent-based approach to illegal maritime behavior modeling Scientific Journals of the Maritime University of Szczecin. 2015, 42 (114): 101-111. DOI: 10.17402/026.
  • Huet T., Osman T, ve Ray C. (2003). Modelling Traffic Navigation Network With A Multi-Agent Platform.In: Proceedings of 17th European Simulation Multiconference. Nottingham, United Kingdom.
  • Jakob, M., Vanek,O., Urban, S., Benda, P. ve Pechoucek, M. (2010). AgentC: Agent-based Testbed for Adversarial Modeling and Reasoning in the Maritime Domain. In: Proc. of 9th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2010). Toronto, Canada.
  • Jakob, M., Vanek, O., Hrstka, O. ve Pechoucek, M.(2012). "Agents vs. Pirates: Multi-Agent Simulation and Optimization to Fight Maritime Piracy. In: Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems – Innovative Applications Track (AAMAS 2012), Valencia, Spain.
  • Koçak, A. ve Arun, Ö. (2006). İçerik Analizi Çalışmalarında Örneklem Sorunu, Selçuk İletişim, Cilt:4, Sayı: 3, 21-28.
  • Kızıltepe, Z. (2015). İçerik Analizi. Seggie, F.G. ve Bayyurt, Y. (Ed.) Nitel araştırma: yöntem, teknik, analiz ve yaklaşımları (s.253-266). Ankara: Anı Yayıncılık.
  • M., Vanĕk O., Pĕchouček M. (2011). Using Agents to Improve International Maritime Transport Security. IEEE Intelligent Systems, 26 (1), 90-96.
  • Macal, C.M. ve North, M.J. (2007). Agent-based modeling and simulation: Desktop ABMS. In: Proceedings of the 2007 Winter Simulation Conference. Washington. USA. DOI: 10.1109/WSC.2007.4419592
  • Monteiro de Farias, O.L. ve Leite, LT. (2006). Simulation and control of maritime area through multi-agent systems and geographical ınformation systems. In: Proceedings of the 2005 International Conference on Computational Intelligence for Modelling, Control and Automation, and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC’05). Vienna, Austria. DOI: 10.1109/CIMCA.2005.1631351.
  • Ni, B., Li, Z., Zhang, P. ve Li, X. (2017). An evacuation model for passenger ships that includes the influence of obstacles in cabins. Hindawi Mathematical Problems in Engineering, Volume 2017, 1-21. DOI: 10.1155/2017/5907876.
  • Onggo, B.S. ve Karatas, M. (2016). “Test-Driven Simulation Modelling: A Case Study Using Agent-Based Maritime Search-Operation Simulation. European Journal Of Operational Research, 254 (2): 517-531. DOI: 10.1016/j.ejor.2016.03.050.
  • Öztanrıseven, F. (2016). Modeling economic impacts of the inland waterway transportation system. Doktora Tezi. University of Arkansas, Industrial Engineering, Arkansas.
  • Parrott, L., Chion, C., Martins, C.A. , Lamontagne, P., Turgeon, S., Landry, J.A., Zhens, B., Marceau, D.J., Michaud, R., Cantin, G., Ménard, N. ve Dionne, S. (2011). A decision support system to assist the sustainable management of navigation activities in the St. Lawrence River Estuary, Canada .Environmental Modelling & Software, 26 (2011): 1403-1418. DOI:10.1016/j.envsoft.2011.08.009.
  • Pidd, M. (2004). Computer simulation in management science 5th edition. Chichster: John Wiley ve Sons Ltd.
  • Railsback, S.F., Lytinen, S.L. ve Jackson, S.K. (2006). Agent-based Simulation Platforms: Review and Development Recommendations. Simulation, 82(9). 609-623. DOI: 10.1177/0037549706073695.
  • Rebollo, M., Julián, V., Carrascosa, C. ve Botti, V.J. (2000). In A Multi-Agent System for the Automation of a Port Container Terminal. In: Proceeding of Workshop i n Agents in Industry. Barcelona, İspanya.
  • Shannon, R.E. (1992). Introduction to simulation. In: Proceedings of the 24th conference on Winter simulation (WSC '92). New York. USA. DOI: 10.1145/167293.167302.
  • Sang L.Z., Tong, X.P., Xu W.X., Mao,Z. ve Yan, X.P. (2017). An agent-based simulation on navigational capacity of multi-bridge waterways. Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment, 231(1):200–211. DOI: 10.1177/1475090216635681.
  • Sharif, O. (2013). Application of agent-based approaches to enhance container terminal Operations. Doktora Tezi, College of Engineering and Computing, University of South Carolina, Columbia.
  • Sinha-Ray,P., Carter, J., Field,T., Marshall, J., Polak,P., Schumacher,K., Song,D., Woods,J., ve Zhang, J.P (2003). Container world: Global agent-based modelling of the container transport business. In: Proceedings 4th Workshop on Agent-Based Simulation. Montpellier, France.
  • Sterman, J. (2000). Business Dynamics: Systems Thinking And Modelling For A Complex World. New York: Mcgraw-Hill.
  • Stuer-Lauridsen, F., Drillet,G., Hansen, F.T., Saunders, J. (2018). Same Risk Area: An area-based approach for the management of bioinvasion risks from ships' ballast water. Marine Policy, 97:147-155.
  • Teng T-H, Lau H.C. ve Kumar, A. (2017). A Multi-Agent System for Coordinating Vessel Traffic (Demonstration). In: Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2017). Sao Paulo, Brazil.
  • Thurston, T. ve Hu, H. (2002). Distributed agent architecture for port automation. In: Proceeding of Twenty-Sixth International Computer Software and Applications Conference. Oxford, UK. DOI:10.1109/CMPSAC.2002.1044537.
  • Vanek, O., Jakob, M. ve Hrstka,O. (2011). Using multi-agent simulation for security of maritime transit. In: Proceedings of Multi-Agent-Based Simulation XII InternationalWorkshop, MABS 2011. Taipei, Taiwan.
  • Vanek, O., Jakob M., Hrstka O. ve Pechoucek, M. (2013). Agent-based model of maritime traffic in piracy-affected waters. Transportation Research Part C, 36 (2013): 157–176.
  • Varol, A.E. (2012). Simulation modeling of maritime piracy using hybrid agent based and discrete event simulation, Yüksek Lisans Tezi, Deniz Harp Okulu Komutanlığı, Deniz Bilimleri ve Mühendisliği Enstitüsü, İstanbul.
  • Varol, A. E. ve Günal, M. M. (2013). Simulation Modeling of Maritime Piracy Using Hybrid Agent Based And Dıscrete Event Simulation. In: Proceedings of the 3rd International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH-2013). ReykJavik. Iceland. DOI: 10.5220/0004431004380445.
  • Varol, A. E. ve Günal, M. M. (2015). Simulating prevention operations at sea against maritime piracy. The Journal of the Operational Research Society, 66(12), 2037-2049.
  • Xiao F., Ligteringen H., Gulijk C.V. ve Ale B. (2012). Artificial force fields for multi-agent simulations of maritime traffic and risk estimation. In: Proceeding of 11th International Probabilistic Safety Assessment and Management Conference ve ESREL 2012. Helsinki. Finland.
  • Xiao, F., Ligteringen, H., Gulijk, C. ve Alevd, B. (2013) Nautical traffic simulation with multi-agent system for safety. In Proceedings of the 16th International IEEE Annual Conference on Intelligent Transportation Systems (ITSC 2013), The Hague, The Netherlands, DOI: 10.1109/ITSC.2013.6728402.
  • Xiao, F. (2014). Ships in an artificial force field: A multi-agent system for nautical traffic and safety. Doktora Tezi. Delft University of Technology- Faculty of Technology, Policy and Management, Netherlands.
  • Xiao Z., Fu X., Zhang L., Ponnambalam L. ve Mong Goh R. S. (2017). Data-driven Multi-Agent System for Maritime Traffic Safety Management. In: Proceeding of 20th International Conference on Intelligent Transportation Systems (ITSC). Yokohama. Japan.
  • Wang, P., Li, G., Ju, R., ve Peng, Y. (2017). Random finite set based data assimilation for dynamic data driven simulation of maritime pirate activity. Mathematical Problems in Engineering, 2017: 1-18.
  • Wasesa, M., Nijdam, P., Muhammad, I.H. ve Heck, E. (2012). Improving the pre-notification protocol of the containers pick-up procedure: An agent-based approach. In: Proceeding of International Conference on Agents and Artificial Intelligence ICAART (2). Algarve, Portugal. DOI: 10.5220/0003742401900196. Wilensky, U. ve Rand, W. (2015). An Introduction to Agent-Based Modeling- Modeling Natural, Social, and Engineered Complex Systems with NetLogo. London: The MIT Press.
  • Wu, Bing, W., Xinping, Y., Wang, Y. ve Xiaoyang W. (2014). Maritime emergency simulation system (MESS) - a virtual decision support platform for emergency response of maritime accidents. In: Proceeding of 2014 4th International Conference On Simulation ve Modeling Methodologies, Technologies ve Applications (SIMULTECH), Vienna. Austria. DOI: 10.5220/0005039401550162.
  • Yıldırım, A. ve Şimşek, H. (2013). Sosyal bilimlerde nitel araştırma yöntemleri, Ankara: Seçkin Yayıncılık. 9.Baskı.
  • Yıldırım, A. ve Şimşek, H. (2016). Sosyal bilimlerde nitel araştırma yöntemleri, Ankara: Seçkin Yayıncılık.
  • Zhang, H., Xiao Y.J. ve Li S . (2009). Agent based simulation architecture for ships' routeing. In: Proceeding of International Conference on Computer and Automation Engineering. Bangkok. Thailand. DOI: 10.1109/ICCAE.2009.24.
  • Zhao, M., Yao, X., Sun, J., Zhang, S. ve Bai, J. (2019). GIS-based simulation methodology for evaluating ship encounters probability to improve maritime traffic safety. IEEE Transactions on Intelligent Transportation Systems, 20(1): 323-337.
  • İnternet Kaynakları
  • Macal, C.M. ve North, M.J. 2006. Introduction to agent-based modeling and Simulation. MCS LANS Informal Seminar November 29, 2006. https://www.mcs.anl.gov/~leyffer/listn/slides-06/MacalNorth.pdf, Erişim Tarihi: 04.02.2019.
  • Maidstone, R. (2012). Discrete event simulation, system dynamics and agent based simulation: discussion and comparison. System 1 (6) Poster. https://personalpages.manchester.ac.uk/staff/robert.maidstone/poster1.pdf Erişim Tarihi: 06.02.2019.
Toplam 62 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Makaleler
Yazarlar

Burcu Çelik Bu kişi benim

Yusuf Zorba

Yayımlanma Tarihi 16 Aralık 2019
Yayımlandığı Sayı Yıl 2019

Kaynak Göster

APA Çelik, B., & Zorba, Y. (2019). DENİZ ULAŞTIRMASINDA ETMEN TABANLI MODELLEME VE BENZETİM İNCELEMESİ. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi, 11(2), 151-176. https://doi.org/10.18613/deudfd.659801
AMA Çelik B, Zorba Y. DENİZ ULAŞTIRMASINDA ETMEN TABANLI MODELLEME VE BENZETİM İNCELEMESİ. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi. Aralık 2019;11(2):151-176. doi:10.18613/deudfd.659801
Chicago Çelik, Burcu, ve Yusuf Zorba. “DENİZ ULAŞTIRMASINDA ETMEN TABANLI MODELLEME VE BENZETİM İNCELEMESİ”. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi 11, sy. 2 (Aralık 2019): 151-76. https://doi.org/10.18613/deudfd.659801.
EndNote Çelik B, Zorba Y (01 Aralık 2019) DENİZ ULAŞTIRMASINDA ETMEN TABANLI MODELLEME VE BENZETİM İNCELEMESİ. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi 11 2 151–176.
IEEE B. Çelik ve Y. Zorba, “DENİZ ULAŞTIRMASINDA ETMEN TABANLI MODELLEME VE BENZETİM İNCELEMESİ”, Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi, c. 11, sy. 2, ss. 151–176, 2019, doi: 10.18613/deudfd.659801.
ISNAD Çelik, Burcu - Zorba, Yusuf. “DENİZ ULAŞTIRMASINDA ETMEN TABANLI MODELLEME VE BENZETİM İNCELEMESİ”. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi 11/2 (Aralık 2019), 151-176. https://doi.org/10.18613/deudfd.659801.
JAMA Çelik B, Zorba Y. DENİZ ULAŞTIRMASINDA ETMEN TABANLI MODELLEME VE BENZETİM İNCELEMESİ. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi. 2019;11:151–176.
MLA Çelik, Burcu ve Yusuf Zorba. “DENİZ ULAŞTIRMASINDA ETMEN TABANLI MODELLEME VE BENZETİM İNCELEMESİ”. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi, c. 11, sy. 2, 2019, ss. 151-76, doi:10.18613/deudfd.659801.
Vancouver Çelik B, Zorba Y. DENİZ ULAŞTIRMASINDA ETMEN TABANLI MODELLEME VE BENZETİM İNCELEMESİ. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi. 2019;11(2):151-76.

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