Multi-objective optimization in computational intelligence theory and practice /

• Corporate Author: IGI Global.
• Other Authors: Alam, Sameer., Bui, Lam Thu.
• Format: Electronic
• Language: English
• Published: Hershey, Pa. : IGI Global (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA), c2008.
• Subjects: Computational intelligence.; Evolutionary computation.; Mathematical optimization.; Artificial intelligence.; Artificial immune systems; Combinatorial optimization; Differential evolution; Evolutionary algorithms; Evolutionary population dynamics; Fundamentals of multi-objective optimization; Lexicographic goal programming; Multi-objective optimization and assignment problems; Multi-objective optimization and bioinformatics; Multi-objective optimization and design of energy systems; Multi-objective optimization and embedded system design; Multi-objective optimization and machine learning; Multi-objective optimization and military applications; Multi-objective optimization and network design; Multi-objective optimization and robotics; Multi-objective optimization for engineering and design; Particle swarm optimization and swam intelligence; Performance assessment techniques; Scatter search and hybridization
• Online Access: View fulltext via EzAccess
• Physical Description: electronic texts (xix, 475 p. : ill.) : digital files.; Also available in print.
• Format: Mode of access: World Wide Web.
• Bibliography: Includes bibliographical references (p. 430-460) and index.
• ISBN: 1599045001 (ebook); 9781599045009 (ebook)
• Access: Restricted to subscribers or individual electronic text purchasers.

Multi-objective optimization (MO) is a fast-developing field in computational intelligence research. Giving decision makers more options to choose from using some post-analysis preference information, there are a number of competitive MO techniques with an increasingly large number of MO real-world applications. This book explores the theoretical, as well as empirical, performance of MOs on a wide range of optimization issues including combinatorial, real-valued, dynamic, and noisy problems. This book provides scholars, academics, and practitioners with a fundamental, comprehensive collection of research on multi-objective optimization techniques, applications, and practices.