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Sinopsis
In this book we present a new optimization algorithm, the proposed algorithm operates in two phases: in the first one, multiobjective version of genetic algorithm is used as search engine in order to generate approximate true Pareto front. This algorithm based on concept of co-evolution and repair algorithm for handling nonlinear constraints. Also it maintains a finite-sized archive of non-dominated solutions which gets iteratively updated in the presence of new solutions based on the concept of ε-dominance. Then, in the second stage, rough set theory is adopted as local search engine in order to improve the spread of the solutions found so far. The results, provided by the proposed algorithm for benchmark problems, are promising when compared with exiting well-known algorithms. Also, our results suggest that our algorithm is better applicable for solving real-world application problems (Economic Environmental Dispatch of Power Systems).
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Reseña del editor
In this book we present a new optimization algorithm, the proposed algorithm operates in two phases: in the first one, multiobjective version of genetic algorithm is used as search engine in order to generate approximate true Pareto front. This algorithm based on concept of co-evolution and repair algorithm for handling nonlinear constraints. Also it maintains a finite-sized archive of non-dominated solutions which gets iteratively updated in the presence of new solutions based on the concept of ε-dominance. Then, in the second stage, rough set theory is adopted as local search engine in order to improve the spread of the solutions found so far. The results, provided by the proposed algorithm for benchmark problems, are promising when compared with exiting well-known algorithms. Also, our results suggest that our algorithm is better applicable for solving real-world application problems (Economic Environmental Dispatch of Power Systems).
Biografía del autor
Dr. Eng. Mohamed Abd Elsameea Hussein received the B.Sc. degree in Electrical Engineering and M.Sc. ,PhD. in Engineering Mathematics from Faculty of Engineering, Menoufiya University, Egypt. His current research interests include: Evolutionary Multiobjective Optimization,Genetic Algorithms, Rough Set and Numerical Optimization.
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- EditorialLAP LAMBERT Academic Publishing
- Año de publicación2016
- ISBN 10 3659846856
- ISBN 13 9783659846854
- EncuadernaciónTapa blanda
- IdiomaInglés
- Número de páginas128
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Multiobjective Optimization Based on Rough Set Theory
Publicado por
LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659846856
ISBN 13: 9783659846854
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Tapa blanda
Librería: moluna, Greven, Alemania
Calificación del vendedor: 5 de 5 estrellas
Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Abd Elsameea Hussein MohamedDr. Eng. Mohamed Abd Elsameea Hussein received the B.Sc. degree in Electrical Engineering and M.Sc. ,PhD. in Engineering Mathematics from Faculty of Engineering, Menoufiya University, Egypt. His current re. Nº de ref. del artículo: 158124636
Cantidad disponible: Más de 20 disponibles
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Multiobjective Optimization Based on Rough Set Theory
Publicado por
LAP LAMBERT Academic Publishing Feb 2016, 2016
ISBN 10: 3659846856
ISBN 13: 9783659846854
Nuevo
Taschenbuch
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In this book we present a new optimization algorithm, the proposed algorithm operates in two phases: in the first one, multiobjective version of genetic algorithm is used as search engine in order to generate approximate true Pareto front. This algorithm based on concept of co-evolution and repair algorithm for handling nonlinear constraints. Also it maintains a finite-sized archive of non-dominated solutions which gets iteratively updated in the presence of new solutions based on the concept of -dominance. Then, in the second stage, rough set theory is adopted as local search engine in order to improve the spread of the solutions found so far. The results, provided by the proposed algorithm for benchmark problems, are promising when compared with exiting well-known algorithms. Also, our results suggest that our algorithm is better applicable for solving real-world application problems (Economic Environmental Dispatch of Power Systems). 128 pp. Englisch. Nº de ref. del artículo: 9783659846854
Cantidad disponible: 2 disponibles
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Multiobjective Optimization Based on Rough Set Theory : Methodology and Application
Publicado por
LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659846856
ISBN 13: 9783659846854
Nuevo
Taschenbuch
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this book we present a new optimization algorithm, the proposed algorithm operates in two phases: in the first one, multiobjective version of genetic algorithm is used as search engine in order to generate approximate true Pareto front. This algorithm based on concept of co-evolution and repair algorithm for handling nonlinear constraints. Also it maintains a finite-sized archive of non-dominated solutions which gets iteratively updated in the presence of new solutions based on the concept of -dominance. Then, in the second stage, rough set theory is adopted as local search engine in order to improve the spread of the solutions found so far. The results, provided by the proposed algorithm for benchmark problems, are promising when compared with exiting well-known algorithms. Also, our results suggest that our algorithm is better applicable for solving real-world application problems (Economic Environmental Dispatch of Power Systems). Nº de ref. del artículo: 9783659846854
Cantidad disponible: 1 disponibles
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Multiobjective Optimization Based on Rough Set Theory
Publicado por
LAP LAMBERT Academic Publishing Feb 2016, 2016
ISBN 10: 3659846856
ISBN 13: 9783659846854
Nuevo
Taschenbuch
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. Neuware -In this book we present a new optimization algorithm, the proposed algorithm operates in two phases: in the first one, multiobjective version of genetic algorithm is used as search engine in order to generate approximate true Pareto front. This algorithm based on concept of co-evolution and repair algorithm for handling nonlinear constraints. Also it maintains a finite-sized archive of non-dominated solutions which gets iteratively updated in the presence of new solutions based on the concept of ¿-dominance. Then, in the second stage, rough set theory is adopted as local search engine in order to improve the spread of the solutions found so far. The results, provided by the proposed algorithm for benchmark problems, are promising when compared with exiting well-known algorithms. Also, our results suggest that our algorithm is better applicable for solving real-world application problems (Economic Environmental Dispatch of Power Systems).Books on Demand GmbH, Überseering 33, 22297 Hamburg 128 pp. Englisch. Nº de ref. del artículo: 9783659846854
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Multiobjective Optimization Based on Rough Set Theory: Methodology and Application
Publicado por
LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659846856
ISBN 13: 9783659846854
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Librería: Revaluation Books, Exeter, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: Brand New. 128 pages. 8.66x5.91x0.29 inches. In Stock. Nº de ref. del artículo: 3659846856
Cantidad disponible: 1 disponibles
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Multiobjective Optimization Based on Rough Set Theory: Methodology and Application
Publicado por
LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659846856
ISBN 13: 9783659846854
Nuevo
paperback
Librería: dsmbooks, Liverpool, Reino Unido
Calificación del vendedor: 4 de 5 estrellas
paperback. Condición: New. New. book. Nº de ref. del artículo: D8S0-3-M-3659846856-6
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