Multiobjective Evolutionary Algorithms and Applications / Advanced Information and Knowledge Processing (PDF)
(Sprache: Englisch)
Evolutionary multiobjective optimization is currently gaining a lot of attention, particularly for researchers in the evolutionary computation communities.
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Evolutionary multiobjective optimization is currently gaining a lot of attention, particularly for researchers in the evolutionary computation communities.
Covers the authors' recent research in the area of multiobjective evolutionary algorithms as well as its practical applications.
Inhaltsverzeichnis zu „Multiobjective Evolutionary Algorithms and Applications / Advanced Information and Knowledge Processing (PDF)“
Preface.- Introduction.- Review of MOEAs.- Conceptual Framework and Distribution Preservation Mechanisms for MOEAs.- Dynamic Population Size and Local Exploration for MOEAs.- A Distributed Cooperative Co-evolutionary Multiobjective Algorithm.- Learning the Search Range in Dynamic Environments.- Performance Assessment and Comparison of MOEAs.- A Multiobjective Evolutionary Algorithm Toolbox.- Evolutionary Computer-Aided Control System Design.- Evolutionary Design Automation for Multivariable QFT Control System.- Evolutionary Design of a HDD Control System.- Evolutionary Scheduling - VRPTW.- Evolutionary Scheduling - TTVRP.- Bibliography.- Index.
Bibliographische Angaben
- Autoren: Kay Chen Tan , Eik Fun Khor , Tong Heng Lee
- 2005, 2005, 296 Seiten, Englisch
- Verlag: Springer-Verlag GmbH
- ISBN-10: 1846281326
- ISBN-13: 9781846281327
- Erscheinungsdatum: 28.11.2005
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- Dateiformat: PDF
- Grösse: 144 MB
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Sprache:
Englisch
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