Sinossi
Evolutionary algorithms (EAs) have grown into a mature field of research in optimization, and have proven to be effective and robust problem-solvers for a broad range of static real-world optimization problems. Yet, since they are based on the principles of natural evolution, and since natural evolution is a dynamic process in a changing environment, EAs are also well suited to dynamic optimization problems. This volume provides a survey on research in the area and shows how EAs can be used to: continuously and efficiently adapt a solution to a changing environment; find a trade-off between solution quality and adaptation cost; find robust solutions whose quality is insensitive to changes in the environment; and find flexible solutions that can be easily adapted when necessary. This resource should prove useful to researchers and professionals who are dealing with dynamic and stochastic optimization problems, and who are interested in applying local search heuristics, such as evolutionary algorithms.
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Contenuti
Preface. 1. Brief Introduction to Evolutionary Algorithms. Part I: Enabling Continuous Adaptation. 2. Optimization in Dynamic Environments. 3. Survey: State of the Art. 4. From Memory to Self-Organization. 5. Empirical Evaluation. 6. Summary of Part I. Part II: Considering Adaptation Cost. 7. Adaptation Cost vs. Solution Quality. Part III: Robustness and Flexibility - Precaution against Changes. 8. Searching for Robust Solutions. 9. From Robustness to Flexibility. 10. Summary and Outlook. References. Index.
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Evolutionary Algorithms (EAs) have grown into a mature field of research in optimization, and have proven to be effective and robust problem solvers for a broad range of static real-world optimization problems. Yet, since they are based on the principles. Codice articolo 5970308
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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Evolutionary Algorithms (EAs) have grown into a mature field of research in optimization, and have proven to be effective and robust problem solvers for a broad range of static real-world optimization problems. Yet, since they are based on the principles of natural evolution, and since natural evolution is a dynamic process in a changing environment, EAs are also well suited to dynamic optimization problems. Evolutionary Optimization in Dynamic Environments is the first comprehensive work on the application of EAs to dynamic optimization problems. It provides an extensive survey on research in the area and shows how EAs can be successfully used to continuously and efficiently adapt a solution to a changing environment, find a good trade-off between solution quality and adaptation cost, find robust solutions whose quality is insensitive to changes in the environment, find flexible solutions which are not only good but that can be easily adapted when necessary. All four aspects are treated in this book, providing a holistic view on the challenges and opportunities when applying EAs to dynamic optimization problems. The comprehensive and up-to-date coverage of the subject, together with details of latest original research, makes Evolutionary Optimization in Dynamic Environments an invaluable resource for researchers and professionals who are dealing with dynamic and stochastic optimization problems, and who are interested in applying local search heuristics, such as evolutionary algorithms. 228 pp. Englisch. Codice articolo 9780792376316
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Buch. Condizione: Neu. Evolutionary Optimization in Dynamic Environments | Jürgen Branke | Buch | xiv | Englisch | 2001 | Springer | EAN 9780792376316 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. Codice articolo 102651929
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Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Evolutionary Algorithms (EAs) have grown into a mature field of research in optimization, and have proven to be effective and robust problem solvers for a broad range of static real-world optimization problems. Yet, since they are based on the principles of natural evolution, and since natural evolution is a dynamic process in a changing environment, EAs are also well suited to dynamic optimization problems. Evolutionary Optimization in Dynamic Environments is the first comprehensive work on the application of EAs to dynamic optimization problems. It provides an extensive survey on research in the area and shows how EAs can be successfully used to continuously and efficiently adapt a solution to a changing environmentfind a good trade-off between solution quality and adaptation costfind robust solutions whose quality is insensitive to changes in the environmentfind flexible solutions which are not only good but that can be easily adapted when necessary.All four aspects are treated in this book, providing a holistic view on the challenges and opportunities when applying EAs to dynamic optimization problems. The comprehensive and up-to-date coverage of the subject, together with details of latest original research, makes Evolutionary Optimization in Dynamic Environments an invaluable resource for researchers and professionals who are dealing with dynamic and stochastic optimization problems, and who are interested in applying local search heuristics, such as evolutionary algorithms.Libri GmbH, Europaallee 1, 36244 Bad Hersfeld 228 pp. Englisch. Codice articolo 9780792376316
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