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Multiobjective Optimization Based on Rough Set Theory: Methodology and Application - Softcover

 
9783659846854: Multiobjective Optimization Based on Rough Set Theory: Methodology and Application

Synopsis

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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About the Author

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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  • PublisherLAP LAMBERT Academic Publishing
  • Publication date2016
  • ISBN 10 3659846856
  • ISBN 13 9783659846854
  • BindingPaperback
  • LanguageEnglish
  • Number of pages128

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Taschenbuch. Condition: 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. Seller Inventory # 9783659846854

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Taschenbuch. Condition: 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). Seller Inventory # 9783659846854

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Condition: 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. Seller Inventory # 158124636

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Taschenbuch. Condition: 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. Seller Inventory # 9783659846854

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Abd Elsameea Hussein, Mohamed, Allah A. Mousa, Abd, A. Elsaw
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