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Sprache: Englisch
Verlag: LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659846856 ISBN 13: 9783659846854
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In den WarenkorbZustand: New. Kit Sang Tang received his BSc from the University of Hong Kong in 1988 and his MSc and PhD from City University of Hong Kong in 1992 and 1996, respectively. He is currently an associate professor in the Department of Electronic Engineer.
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Verlag: Lap Lambert Academic Publishing, 2011
ISBN 10: 3846548898 ISBN 13: 9783846548899
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In den WarenkorbGebunden. Zustand: New. Kit Sang Tang received his BSc from the University of Hong Kong in 1988 and his MSc and PhD from City University of Hong Kong in 1992 and 1996, respectively. He is currently an associate professor in the Department of Electronic Engineer.
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Verlag: LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659846856 ISBN 13: 9783659846854
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Taschenbuch. Zustand: 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).
Sprache: Englisch
Verlag: LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3846548898 ISBN 13: 9783846548899
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Many real-world problems involve two types of problem difficulty: I) multiple, conflicting objectives and II) a highly complex search space. On the one hand, instead of a single optimal solution competing goals give rise to a set of compromise solutions, generally denoted as Pareto-optimal. In the absence of preference information, none of the corresponding trade-offs can be said to be better than the others. On the other hand, the search space can be too large and too complex to be solved by exact methods. Thus, efficient optimization strategies are required that are able to deal with both difficulties. Evolutionary algorithms possess several characteristics that are desirable for this kind of problem and make them preferable to classical optimization methods. In fact, various evolutionary approaches to multiobjective optimization have been proposed since 1985, capable of searching for multiple Pareto optimal solutions concurrently in a single simulation run. The subject of this work is the improvement of multiobjective evolutionary algorithms and their application to engineering problems.
Sprache: Englisch
Verlag: LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3846548898 ISBN 13: 9783846548899
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Taschenbuch. Zustand: Neu. Study on multiobjective optimization using improved genetic Algorithm | Methodology and Application | Abd Allah A. Mousa | Taschenbuch | 144 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783846548899 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu Print on Demand.
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In den WarenkorbZustand: New. pp. 279 16 page color insert - 19 color figures follows page 148 This item is printed on demand.