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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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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.
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Verlag: Taylor & Francis Ltd Mär 2018, 2018
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Taschenbuch. Zustand: Neu. Neuware.
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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.
Sprache: Englisch
Verlag: LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3846548898 ISBN 13: 9783846548899
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Sprache: Englisch
Verlag: Taylor & Francis Inc Mai 2012, 2012
ISBN 10: 1439899193 ISBN 13: 9781439899199
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Buch. Zustand: Neu. Neuware - The first book to focus on jumping genes outside bioscience and medicine, Multiobjective Optimization Methodology: A Jumping Gene Approach introduces jumping gene algorithms designed to supply adequate, viable solutions to multiobjective problems quickly and with low computational cost. Better Convergence and a Wider Spread of Nondominated Solutions The book begins with a thorough review of state-of-the-art multiobjective optimization techniques. For readers who may not be familiar with the bioscience behind the jumping gene, it then outlines the basic biological gene transposition process and explains the translation of the copy-and-paste and cut-and-paste operations into a computable language. To justify the scientific standing of the jumping genes algorithms, the book provides rigorous mathematical derivations of the jumping genes operations based on schema theory. It also discusses a number of convergence and diversity performance metrics for measuring the usefulness of the algorithms.Practical Applications of Jumping Gene Algorithms Three practical engineering applications showcase the effectiveness of the jumping gene algorithms in terms of the crucial trade-off between convergence and diversity. The examples deal with the placement of radio-to-fiber repeaters in wireless local-loop systems, the management of resources in WCDMA systems, and the placement of base stations in wireless local-area networks. Offering insight into multiobjective optimization, the authors show how jumping gene algorithms are a useful addition to existing evolutionary algorithms, particularly to obtain quick convergence solutions and solutions to outliers.
Sprache: Englisch
Verlag: LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659846856 ISBN 13: 9783659846854
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
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).