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Multi-Objective Memetic Algorithms [Hardcover]

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  • Category: Books (Computers)
  • ISBN-10:  354088050X
  • ISBN-10:  354088050X
  • ISBN-13:  9783540880509
  • ISBN-13:  9783540880509
  • Publisher:  Springer
  • Publisher:  Springer
  • Pages:  404
  • Pages:  404
  • Binding:  Hardcover
  • Binding:  Hardcover
  • Pub Date:  01-Feb-2009
  • Pub Date:  01-Feb-2009
  • SKU:  354088050X-11-SPRI
  • SKU:  354088050X-11-SPRI
  • Item ID: 100514289
  • List Price: $169.99
  • Seller: ShopSpell
  • Ships in: 5 business days
  • Transit time: Up to 5 business days
  • Delivery by: Jul 04 to Jul 06
  • Notes: Brand New Book. Order Now.

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.

Memetic algorithms are a success story in sophisticated evolutionary computing. Written for as wide a readership as possible, this book reflects the current state-of-the-art in the theory and practice of Memetic algorithms and is an invaluable reference.

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.

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