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Evolutionary Computation and Global Optimization (10; Krajowa Konferencja Algorytmy Ewolucyjne i Optymalizacja Globalna; 11-13.06.2007; Będlewo, Poland)
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Abstrakty
This document describes possible applicationof MultiObjective Evolutionary Algorithms (MOEAs) to a problem of finding the most sutiable vesel route taking into account changeable weather conditions and several navigational constraints. The paper includes a review of MOEA-specific techniques and presents a proposal of their utilizaytion in a weather routing evolutionary algorithm.
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Tom
Strony
277--284
Opis fizyczny
Bibliogr. 9 poz.
Twórcy
Bibliografia
- [1] Goldberg, D.E. Genetic Algorithms in Search, Optimization and Machine Learning, Addision Wesley, Reading, 1987.
- [2] Hagiwara, H. Weather routing of (sail-assisted) motor vessels, PhD thesis. Delft, 1989.
- [3] James, R.W. Application of wave forecast to marine navigation, US Navy Hydrographic Office, Washington, 1957.
- [4] Michalewicz, Z. Genetic Algorithms + Data Structure = Evolution Programs, Springer-Verlag Berlin Heidelberg, 1996.
- [5] Purshouse, R.C., Fleming, P.J. The MultiObjective Genetic Algorithm applied to benchmark problems - an analysis, Research Report No. 796, University of Sheffield, 2001.
- [6] Smierzchalski, R., Michalewicz, Z. Modeling of a Ship Trajectory in Collision Situations at Sea by Evolutionary Algorithm, IEEE Transactions on Evolutionary Computation No. 3 Vol. 4, pp. 227-241, 2000.
- [7] Van Veldhuizen, D.A., Lamont, G.B. Multiobjective Evolutionary Algorithms: Analyzing the State-of-the-Art, Evolutionary Computation, pp.125-147, Massachusets Institute of Technology, 2000.
- [8] Wisniewski, B. Methods of route selection for a sea going vessel (in Polish), Wydawnictwo Morskie, Gdańsk, 1991.
- [9] Zitzler, E., Thiele, L. Multiobjective Evolutionary Algorithms: A Comparative Case Study and the Strength Pareto Approach, IEEE Transactions on Evolutionary Computation No. 3 Vol. 4, pp. 257-271, 1999.
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Bibliografia
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bwmeta1.element.baztech-article-PWA6-0041-0014