Multiobjective optimization based rough par abd elsameea (5 résultats)

Taschenbuch. Etat : Neu. Multiobjective Optimization Based on Rough Set Theory | Methodology and Application | Mohamed Abd Elsameea Hussein (u. a.) | Taschenbuch | 128 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783659846854 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

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Taschenbuch. Etat : 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.…

Etat : 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.…

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. 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).VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 128 pp. Englisch.…