A PSO Approach to Navigational Shortest Path Problem on an Experience-Based Network Model of the Aegean Sea

Öz

Finding shortest routes for commercial vessels has ever been an important issue on marine science. Shortest route means less sailing time, less sailing time means faster delivery of cargo, less consumption of fuel, less human power. In this study, we present a particle swarm optimization approach to navigational decision support system. The study is applied on the Aegean Sea. The proposed system is a dynamic decision support system that calculates the shortest path from any starting node to any finishing node. The network model consists of 604 nodes. Any ship using this system can find the shortest route to finishing node dynamically.

Anahtar Kelimeler

• particle swarm optimization
• decision support system
• shortest path
• aegean sea

A PSO Approach to Navigational Shortest Path Problem on an Experience-Based Network Model of the Aegean Sea

Öz

Kaynakça

1. Referans1 Fossen, Thor I. Encyclopedia of Systems and Control, pp.1-9. Mathematical Models of Ships and Underwater Vehicles,2011.
2. Referans2 nomoioxxe. Prefectures HEMCO (Shapefile),25/12/2016. http://services.opendatagortynia.gr//geoserver// wfsrequestGetFeature servicewfs version1.0.0 typenamegortynia:NOMOI-OKXE.
3. Referans3 turkeyshapefile. European Environment Agency,26/12/2016. https://www.eea.europa.eu/data-andmaps/data/eea-reference-grids-2/ gis-files/turkey–shapefile.
4. Referans4 INAN, Timur and BABA, Ahmet Fevzi.(Turkish) 2018 Electric Electronics, Computer Science, Biomedical Engineerings’ Meeting (EBBT).Examining the performance of ant colony optimization on shortest path problem: (Aegean sea example).2018
5. Referans5 INAN, Timur and BABA, Ahmet Fevzi.(Turkish) Marmara Fen Bilimleri Dergisi. Ege Denizinin Detaylı Bir Du¨g˘um¨ Haritasının Kullanılarak Genetik Algoritma ˙Ile En Kısa Yol Sonuc¸larının Elde Edilmesi.2018
6. Referans6 Koromila, Ioanna and Nivolianitou, Zoe and Giannakopoulos, Theodoros. Bayesian network to predict environmental risk of a possible ship accident. ACM International Conference Proceeding Series.2016
7. Referans7 Kosmas O.T.,Vlachos D.S. Simulated annealing for optimal ship routing. Computers and Operations Research.2012
8. Referans8 Veneti A.,Makrygiorgos A., Konstantopoulos c.,Pantziou G., Vetsikas I.A..Minimizing the fuel consumption and the risk in maritime transportation: A bi-objective weather routing approach.Computers and Operations Research.2017

9. Referans9 Kepaptsoglou K.,Fountas G.,Karlaftis M.G. Weather impact on containership routing in closed seas: A chanceconstraint optimization approach.Transportation Research Part C: Emerging Technologies.2015
10. Referans10 Nikolaos Alexandris and Chrysostomos Fountas and Aristidis Vlachos. The ant colony system: optimization for the logistics of marine cargo in the Aegean. Journal of Statistics and Management Systems.2005
11. Referans11 Zhuo, Yongqiang and Hearn, G.E. Chinese Control and Decision Conference. ,A Ship Based Intelligent AntiCollision Decision-Making Support System Utilizing Trial Manoeuvres,2008.
12. Referans12 Padhy C. P.,Sen D., Bhaskaran P. K. Application of wave model for weather routing of ships in the North Indian Ocean.Natural Hazards.2008
13. Referans13 Tsou, Ming-Cheng and Kao, Sheng-Long and Su, ChienMin. The Journal of Navigation. Decision Support from Genetic Algorithms for Ship Collision Avoidance Route Planning and Alerts,2010.
14. Referans14 Keivan Ghoseiri and Behnam Nadjari. An ant colony optimization algorithm for the bi-objective shortest path problem. Applied Soft Computing.2010.
15. Referans15 F. Araujo and B. Ribeiro and L. Rodrigues. IEEE Transactions on Neural Networks. A neural network for shortest path computation.2001.
16. Referans16 J. Kennedy and R. Eberhart. Neural Networks. Particle swarm optimization, 1995.
17. Referans17 Ammar W. Mohemmed and Nirod Chandra Sahoo and Tan Kim Geok. Applied Soft Computing. Solving shortest path problem using particle swarm optimization,2008.
18. Referans18 Chang Wook Ahn and R. S. Ramakrishna. IEEE Transactions on Evolutionary Computation. A genetic algorithm for shortest path routing problem and the sizing of populations, 2002.
19. Referans19 E. W. Dijkstra (1959). A note on two problems in connexion with graphs. Numerische Mathematik. Vol.1. Pages. 269-271.
20. Referans20 Bellman, E., “On a Routing Problem”, Appl.Math., Vol 16, 87–90, 1958.
21. Referans21 Fossen, T. I. and T. Perez (2004). Marine Systems Simulator (MSS). http://www.marinecontrol.org.