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Multicriteria Evolutionary Weather Routing Algorithm in Practice

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EN
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EN
The Multicriteria Evolutionary Weather Routing Algorithm (MEWRA) has already been introduced by the author on earlier TransNav 2009 and 2011 conferences with a focus on theoretical application to a hybrid‐propulsion or motor‐driven ship. This paper addresses the topic of possible practical weather routing applications of MEWRA. In the paper some practical advantages of utilizing Pareto front as a result of multicriteria optimization in case of route finding are described. The paper describes the notion of Paretooptimality of routes along with a simplified, easy to follow, example. It also discusses a choice of the most suitable ranking method for MEWRA (a comparison between Fuzzy TOPSIS and Zero Unitarization Method is presented). In addition to that the paper briefly outlines a commercial application of MEWRA.
Twórcy
  • Gdynia Maritime University, Gdynia, Poland
Bibliografia
  • [1] Chu T.C. & Lin Y.C. 2003. A Fuzzy TOPSIS Method for Robot Se‐lection, The International Journal Of Advanced Manufacturing Technology. pp. 284‐290. Springer. UK.
  • [2] Hagiwara H. 1989. Weather routing of (sail‐assisted) motor vessels. PhD Thesis. Technical University of Delft. The Netherlands.
  • [3] Hinnenthal J. 2007. Robust Pareto – Optimum Routing of Ships Utilizing Deterministic and Ensemble Weather Forecasts. PhD Thesis. Technical University Berlin. Germany.
  • [4] Kim B.K. & Jo J.B. & Kim J.R. & Gen M.. 2009. Optimal Route Search in Car Navigation Systems by Multiobjective Genetic Algorithms. International Journal of Information Systems for Logistics and Management. Vol. 4, No. 2 (2009) 9‐18. lnderscience Enterprises Ltd. Switzerland.
  • [5] Krata P. & Szlapczynska J. 2012. Weather Hazard Avoidance in Modeling Safety of Motor‐Driven Ship for Multicriteria Weather Routing. TransNav ‐ International Journal on Marine Navigation and Safety of Sea Transportation. Vol. 6. No. 1. pp. 71‐78. Poland.
  • [6] Kukula K. 2000. Zero Unitarization Method. Wydawnictwa Naukowe PWN. Poland. Warszawa 2000.
  • [7] James R.W. 1957. Application of wave forecast to Marine navigation. Washington: US Navy Hydrographic Office.
  • [8] Marie S. & Courteille E. 2009. Multi‐Objective Optimization of Motor Vessel Route. TransNav ‐ International Journal on Marine Navigation and Safety of Sea Transportation. Vol. 3. No. 2. pp. 133‐141. Poland.
  • [9] Spaans J.A. 1986. Windship routeing. Technical University of Delft.
  • [10] Szlapczynska J. 2007. Multiobjective Approach to Weather Routing. TransNav ‐ International Journal on Marine Navigation and Safety of Sea Transportation. Vol. 1. No. 3. pp. 273‐278. Poland.
  • [11] Szlapczynska J. & Smierzchalski R. 2009. Multicriteria Optimisation in Weather Routing. TransNav ‐ International Journal on Marine Navigation and Safety of Sea Transportation. Vol. 3. No. 4. pp. 393‐400. Poland.
  • [12] Szlapczynska J. 2012. Multicriteria Evolutionary Weather Routing Algorithm (MEWRA) Applied to Marine Weather Forecast and Analysis Tool – NaviWeather by NavSim. Proceedings of ENC’ 2012. Polish Navigational Forum. Gdynia. Poland.
  • [13] Wisniewski B. 1991. Methods of route selection for a sea going vessel (in Polish), Gdansk: Wydawnictwo Morskie.
  • [14] Zitzler E. & Thiele L. 1999. Multiobjective Evolutionary Algorithms: A Comparative Case Study and the Strength Pareto Approach. IEEE Transactions on Evolutionary Computation, No. 3, Vol. 4, pp. 257‐271. IEEE Computational Intelligence Society. USA.
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Bibliografia
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