Abstrakt
Multi-criterion, evolutionary and quantum decision making supported by the Adaptive Quantum-based Multi-criterion Evolutionary Algorithm (AQMEA) has been considered for distributed complex systems. AQMEA had been developed to the task assignment problem, and then it has been applied to underwater vehicle planning as another benchmark three-criterion optimization problem. For evaluation of a vehicle trajectory three criteria have been used.
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Informacje szczegółowe
- Kategoria:
- Aktywność konferencyjna
- Typ:
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Tytuł wydania:
- Recent advances in applied and biomedical informatics and computational engineering in system applications : Proceedings of the 11th WSEAS International Conference on Applied Informatics and Communications (AIC'11) : Proceedingd of the 4th ESEAS International Conference on Biomedical Electronics and Biomedical Informatics (BEBI'11) : Proceedings of the International Conference on Environment, Economics, Energy, Devices, Systems, Communications, Computers, Pure and Applied Mathematics, Florence, Italy, August 23-25, 2011 strony 222 - 227
- Język:
- angielski
- Rok wydania:
- 2011
- Opis bibliograficzny:
- Balicki J., Drozda G., Masiejczyk J.: Multi-criterion, evolutionary and quantum decision making in complex systems// Recent advances in applied and biomedical informatics and computational engineering in system applications : Proceedings of the 11th WSEAS International Conference on Applied Informatics and Communications (AIC'11) : Proceedingd of the 4th ESEAS International Conference on Biomedical Electronics and Biomedical Informatics (BEBI'11) : Proceedings of the International Conference on Environment, Economics, Energy, Devices, Systems, Communications, Computers, Pure and Applied Mathematics, Florence, Italy, August 23-25, 2011/ Florence: WSEAS Press, 2011, s.222-227
- Weryfikacja:
- Politechnika Gdańska
wyświetlono 104 razy
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Multi-criterion decision making in distributed systems by quantum evolutionary algorithms
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- J. Masiejczyk
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2010