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      Book

      Practical Handbook of Genetic Algorithms
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      Book

      Practical Handbook of Genetic Algorithms

      DOI link for Practical Handbook of Genetic Algorithms

      Practical Handbook of Genetic Algorithms book

      New Frontiers

      Practical Handbook of Genetic Algorithms

      DOI link for Practical Handbook of Genetic Algorithms

      Practical Handbook of Genetic Algorithms book

      New Frontiers
      Edited ByLance Chambers
      Edition 1st Edition
      First Published 1995
      eBook Published 20 December 2019
      Pub. Location Boca Raton
      Imprint CRC Press
      DOI https://doi.org/10.1201/9780429128332
      Pages 464
      eBook ISBN 9780429128332
      Subjects Computer Science
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      Chambers, L. (Ed.). (1995). Practical Handbook of Genetic Algorithms: New Frontiers (1st ed.). CRC Press. https://doi.org/10.1201/9780429128332

      ABSTRACT

      The mathematics employed by genetic algorithms (GAs)are among the most exciting discoveries of the last few decades. But what exactly is a genetic algorithm? A genetic algorithm is a problem-solving method that uses genetics as its model of problem solving. It applies the rules of reproduction, gene crossover, and mutation to pseudo-organism

      TABLE OF CONTENTS

      chapter Chapter A|26 pages

      Multi-Niche Crowding for Multi-Modal Search

      ByV. Rao Vemuri, Walter Cedeño

      chapter Chapter 1|22 pages

      Artificial Neural Network Evolution: Learning to Steer a Land Vehicle

      ByShumeet Baluja

      chapter Chapter 2|14 pages

      Locating Putative Protein Signal Sequences

      Edited ByMichael Levin

      chapter Chapter 3|26 pages

      Selection Methods for Evolutionary Algorithms

      Edited ByPeter J.B. Hancock

      chapter Chapter 4|18 pages

      Parallel Cooperating Genetic Algorithms: An Application to Robot Motion Planning

      Edited ByEl-Ghazali Talbi, Pierre Bessiere, Juan-Manuel Ahuactzin, Emmanuel Mazer

      chapter Chapter 5|28 pages

      The Boltzmann Selection Procedure 1

      ByMichael de la Maza

      chapter Chapter 6|16 pages

      Structure and Performance of Fine-Grain Parallelism in Genetic Search

      Edited ByShumeet Baluja

      chapter Chapter 7|18 pages

      Parameter Estimation for a Generalized Parallel Loop Scheduling Algorithm

      Edited ByKelvin K. Yue, David J. Lilja

      chapter Chapter 8|24 pages

      Controlling a Dynamic Physical System Using Genetic-Based Learning Methods

      ByM. O. Odetayo, D. Dasgupta

      chapter Chapter 9|22 pages

      A Hybrid Approach Using Neural Networks. Simulation. Genetic Algorithms, and Machine Learning for Real-Time Sequencing and Scheduling Problems

      ByLuis Rabelo, Albert Jones, Yuehwern Yih

      chapter Chapter 10|32 pages

      Chemical Engineering

      Edited ByVijaykumar Hanagandi, Michael Nikolaou

      chapter Chapter 11|26 pages

      Vehicle Routin1 with Time Windows usin1 Genetic Algorithms

      BySam R. Thangiah

      chapter Chapter 12|24 pages

      Evolutionary Algorithms and Dialogue

      Edited ByD.J. Nettleton, R. Garigliano

      chapter Chapter 13|14 pages

      Incorporating Redundancy and Gene Activation Mechanisms in Genetic search for adapting to Non-Stationarv Environments.

      ByDipankar Dasgupta

      chapter Chapter 14|16 pages

      Input Space Segmentation with a Genetic Algorithm for Generation of Rule Based Classifier Systems

      Edited BySaman K. Halgamuge, Manfred Glesner
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