Multi-Objective Memetic Algorithms

Multi-Objective Memetic Algorithms

  • Chi-Keong Goh
  • Yew Soon Ong
  • Kay Chen Tan
Publisher:Springer Science & Business MediaISBN 13: 9783540880509ISBN 10: 354088050X

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Multi-Objective Memetic Algorithms is written by Chi-Keong Goh and published by Springer Science & Business Media. It's available with International Standard Book Number or ISBN identification 354088050X (ISBN 10) and 9783540880509 (ISBN 13).

The application of sophisticated evolutionary computing approaches for solving complex problems with multiple conflicting objectives in science and engineering have increased steadily in the recent years. Within this growing trend, Memetic algorithms are, perhaps, one of the most successful stories, having demonstrated better efficacy in dealing with multi-objective problems as compared to its conventional counterparts. Nonetheless, researchers are only beginning to realize the vast potential of multi-objective Memetic algorithm and there remain many open topics in its design. This book presents a very first comprehensive collection of works, written by leading researchers in the field, and reflects the current state-of-the-art in the theory and practice of multi-objective Memetic algorithms. "Multi-Objective Memetic algorithms" is organized for a wide readership and will be a valuable reference for engineers, researchers, senior undergraduates and graduate students who are interested in the areas of Memetic algorithms and multi-objective optimization.