Kay Chen Tan, Eik Fun Khor, Tong Heng Lee

Multiobjective Evolutionary Algorithms and Applications (eBook, PDF)

• Format: PDF

Produktbeschreibung

Evolutionary multiobjective optimization is currently gaining a lot of attention, particularly for researchers in the evolutionary computation communities. This monograph is suitable as a secondary text for graduate level computational intelligence courses, and as a reference for researchers, lecturers, and practitioners in industry.

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Produktdetails

• Verlag: Springer London
• Seitenzahl: 296
• Erscheinungstermin: 28. November 2005
• Englisch
• ISBN-13: 9781846281327
• Artikelnr.: 37337942

Autorenporträt

Kay Chen Tan, National University of Singapore, Singapore / Eik Fun Khor, National University of Singapore, Singapore / Tong Heng Lee, National University of Singapore, Singapore

Inhaltsangabe

Review of MOEAs.- Conceptual Framework and Distribution Preservation Mechanisms for MOEAs.- Decision Supports and Advanced Features for MOEAs.- Dynamic Population Size and Local Exploration for MOEAs.- A Distributed Cooperative Coevolutionary 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 of Multivariable QFT Control System.- Evolutionary Design of HDD Servo Control System.- Evolutionary Scheduling - VRPTW.- Evolutionary Scheduling - TTVRP.