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Recent Advances in Memetic Algorithms

  • Book
  • © 2005

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Overview

Editors:
  1. William E. Hart

    1. Algorithms and Discrete Mathematics Department, Sandia National Laboratories, Albuquerque, USA

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  2. J. E. Smith

    1. Faculty of Computing, Engineering and Mathematical Sciences, University of the West of England, Bristol, UK

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  3. N. Krasnogor

    1. Automatic Scheduling, Optimisation and Planning Group, School of Computer Science and IT, University of Nottingham, Nottingham, UK

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  • First book focusing on memetic algorithms as the central topical matter
  • Gives a coherent, integrated view on both good practice examples and new trends including a concise and self-contained introduction to memetic algorithms
  • Presents a rich state-of-the-art gallery of works on memetic algorithms
  • Includes supplementary material: sn.pub/extras

Part of the book series: Studies in Fuzziness and Soft Computing (STUDFUZZ, volume 166)

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About this book

Memetic algorithms are evolutionary algorithms that apply a local search process to refine solutions to hard problems. Memetic algorithms are the subject of intense scientific research and have been successfully applied to a multitude of real-world problems ranging from the construction of optimal university exam timetables, to the prediction of protein structures and the optimal design of space-craft trajectories. This monograph presents a rich state-of-the-art gallery of works on memetic algorithms. Recent Advances in Memetic Algorithms is the first book that focuses on this technology as the central topical matter. This book gives a coherent, integrated view on both good practice examples and new trends including a concise and self-contained introduction to memetic algorithms. It is a necessary read for postgraduate students and researchers interested in recent advances in search and optimization technologies based on memetic algorithms, but can also be used as complement to undergraduate textbooks on artificial intelligence.

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Table of contents (16 chapters)

  1. Related Search Technologies

    1. Angels & Mortals: A New Combinatorial Optimization Algorithm

      • Francesc Comellas, Ruben Gallegos
      Pages 397-405
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  2. Back Matter

    Pages 407-408
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Editors and Affiliations

  • Algorithms and Discrete Mathematics Department, Sandia National Laboratories, Albuquerque, USA

    William E. Hart

  • Faculty of Computing, Engineering and Mathematical Sciences, University of the West of England, Bristol, UK

    J. E. Smith

  • Automatic Scheduling, Optimisation and Planning Group, School of Computer Science and IT, University of Nottingham, Nottingham, UK

    N. Krasnogor

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