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Multi-objective weather routing of sailing vessels

Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The paper presents a multi-objective deterministic method of weather routing for sailing vessels. Depending on a particular purpose of sailboat weather routing, the presented method makes it possible to customize the criteria and constraints so as to fit a particular user’s needs. Apart from a typical shortest time criterion, safety and comfort can also be taken into account. Additionally, the method supports dynamic weather data: in its present version short-term, mid-term and long-term term weather forecasts are used during optimization process. In the paper the multi-objective optimization problem is first defined and analysed. Following this, the proposed method solving this problem is described in detail. The method has been implemented as an online SailAssistance application. Some representative examples solutions are presented, emphasizing the effects of applying different criteria or different values of customized parameters.
Słowa kluczowe
Rocznik
Tom
Strony
10--17
Opis fizyczny
Bibliogr. 29 poz., rys., tab.
Twórcy
  • Gdańsk University of Technology 11/12 Narutowicza St. 80 - 233 Gdańsk Poland
  • Gdańsk University of Technology 11/12 Narutowicza St. 80 - 233 Gdańsk Poland
Bibliografia
  • 1. Arribas, F.L.P., A.L. Piniro: Seasickness prediction in passenger ships at the design stage, Ocean Eng. 34 (2007) 2086–2092.
  • 2. Daniel, K., A. Nash, S. Koenig, A. Felner: Theta *: AnyAngle Path Planning on Grids, 39 (2010) 533–579.
  • 3. Dębski, R.: An adaptive multi-spline refinement algorithm in simulation based sailboat trajectory optimization using onboard multi-core computer systems, Int. J. Appl. Math. Comput. Sci. 26 (2016) 351–365.
  • 4. Dijkstra, E.W.: A Note on Two Probles in Connexion with Graphs, Numer. Math. 1 (1959) 269–271.
  • 5. Disser, Y., M. Müller–Hannemann, M. Schnee: Multicriteria Shortest Paths in Time-Dependent Train Networks, in: Exp. Algorithms, Springer Berlin Heidelberg, Berlin, Heidelberg, 2008: pp. 347–361.
  • 6. Geisberger, R.: Advanced Route Planning in Transportation Networks, (2011) 227.
  • 7. Johnson, B.: Operator Guidance Based on Assessing the Wind - Heel Angle Relationship of Traditionally - Rigged Sailing Vessels, (n.d.).
  • 8. Jurdziński, M.: Podstawy Nawigacji Morskiej, Wydawncitwo Akademii Morskiej w Gdyni, 2003.
  • 9. Kerwin, J.: A velocity prediction program for ocean racing yachts revised to February 1978, M.I.T. Ocean Eng. Rep. Number 78-11, MIT, Cambridge, MA. (1978).
  • 10. Lee, T., H. Chung, H. Myung: Multi-resolution path planning for marine surface vehicle considering environmental effects, Ocean. 2011 IEEE - Spain. (2011) 1–9.
  • 11. Lisowski, J.: Sensitivity of Computer Support Game Algorithms, Int. J. Appl. Math. Comput. Sci. 23 (2013) 439–446.
  • 12. Lisowski, J.: ScienceDirect Computational intelligence methods of a safe ship control, Procedia - Procedia Comput. Sci. 35 (2014) 634–643.
  • 13. Mannarini, G., G. Coppini, P. Oddo, N. Pinardi: A Prototype of Ship Routing Decision Support System for an Operational Oceanographic Service, TransNav, Int. J. Mar. Navig. Saf. Sea Transp. 7 (2013) 53–59.
  • 14. Marchaj, C.: Teoria żeglowania. Aerodynamika żagla, IV, Alma-Press Sp. z o.o., Warszawa, 2016.
  • 15. Neumann, T.: Method of Path Selection in the Graph - Case Study, TransNav, Int. J. Mar. Navig. Saf. Sea Transp. 8 (2014) 557–562.
  • 16. Philpott, A., A. Mason: Optimising yacht routes under uncertainty, Proc. 15th Chesap. Sail. Yacht Symp. Annapolis, MD. (2001).
  • 17. Philpott, A.B., R.M. Sullivan, P.S. Jackson: Yacht velocity prediction using mathematical programming, Eur. J. Oper. Res. 67 (1993) 13–24.
  • 18. Ramalingam, G., T. Reps: On the computational complexity of dynamic graph problems, Theor. Comput. Sci. 158 (1996) 233–277.
  • 19. Skriver, A.J.V., K.A. Andersen: A label correcting approach for solving bicriterion shortest-path problems, Comput. Oper. Res. 27 (2000) 507–524.
  • 20. Specht, C., A. Weintrit, M. Specht, Y. Wo: A History of Maritime Radio- Navigation Positioning Systems used in Poland, (2017).
  • 21. Stelzer, R.: Novel Algorithms and Experimental Demonstration, De Montfort University, Leicester, 2012.
  • 22. Stelzer, R., K. Jafarmadar: The robotic sailing boat asv roboat as a maritime research platform, Proc. 22nd Int. HISWA Symp. Yacht Des. Yacht Constr. (2012).
  • 23. Szlapczynska, J.: Multi-objective Weather Routing with Customised Criteria and Constraints, J. Navig. 68 (2015) 338–354.
  • 24. Szlapczynski, R.: A New Method of Ship Routing on Raster Grids, with Turn Penalties and Collision Avoidance, J. Navig. 59 (2006) 27–42.
  • 25. Weintrit, A., P. Kopacz: Computational Algorithms Implemented in Marine Navigation Electronic Systems, in: Springer, Berlin, Heidelberg, 2012: pp. 148–158.
  • 26. Weintrit, A., R. Wawruch: Polish Approach to e-Navigation Concept, Communications. 1 (2007) 327–335.
  • 27. Wilcox, B.H., T. Litwin, J. Biesiadecki, J. Matthews, M. Heverly, J. Morrison, J. Townsend, N. Ahmad, A. Sirota, B. Cooper: ATHLETE: A Cargo Handling and Manipulation Robot for the Moon, J. F. Robot. 24 (2007) 421–434.
  • 28. Życzkowski, M.: Sailing Vessel Routing Considering Safety Zone and Penalty Time for Altering Course, TransNav, Int. J. Mar. Navig. Saf. Sea Transp. 11 (2017) 49–54.
  • 29. Życzkowski, M.: METHOD OF ROUTING SHIPS SAILING IN DEDICATED ENVIRONMENT, Annu. Navig. 24 (2017) 147–159.
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-7546077d-2876-4b5f-974e-510ef6b9a0df
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