Author: Jürgen Branke
Edition: 2002
Publisher: Springer
Binding: Hardcover
ISBN: 0792376315
Category: Programming
List Price: $ 279.00
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Evolutionary Optimization in Dynamic Environments (Genetic Algorithms and Evolutionary Computation)
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. Programming books Evolutionary Optimization in Dynamic Environments pdf. 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. Download books evolutionary optimization in dynamic environments pdf via mediafire, 4shared, rapidshare.
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Evolutionary Optimization in Dynamic Environments, ISBN-13: 9780792376316, ISBN-10: 0792376315
Evolutionary Optimization in Dynamic Environments, ISBN-13: 9780792376316, ISBN-10: 0792376315
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Store Search search Title, ISBN and Author Evolutionary Optimization in Dynamic Environments by Kirby S., Jurgen Branke Estimated delivery 3-12 business days Format Hardcover Condition Brand New 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
Store Search search Title, ISBN and Author Evolutionary Optimization in Dynamic Environments by Kirby S., Jurgen Branke Estimated delivery 3-12 business days Format Hardcover Condition Brand New 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
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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
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
Price: $245.56
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
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
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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
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
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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. Download free Evolutionary Optimization in Dynamic Environments (Genetic Algorithms and Evolutionary Computation) pdf
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