Evolutionary optimization algorithms

Evolutionary optimization algorithms

by Simon, Dan

Type Book
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"This book is a clear and lucid presentation of Evolutionary Algorithms, with a straightforward, bottom-up approach that provides the reader with a firm grasp of the basic principles of EAs. Covering the theory, history, mathematics, and applications of evolutionary optimization algorithms, this timely and practical book offers lengthy examples, a companion website, MATLAB code, and a Solutions Manual--making it perfect for advanced undergraduates, graduates, and practicing engineers involved i…

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Title Statements

  • Full title :Evolutionary optimization algorithms / Dan Simon.

Summary

"This book is a clear and lucid presentation of Evolutionary Algorithms, with a straightforward, bottom-up approach that provides the reader with a firm grasp of the basic principles of EAs. Covering the theory, history, mathematics, and applications of evolutionary optimization algorithms, this timely and practical book offers lengthy examples, a companion website, MATLAB code, and a Solutions Manual--making it perfect for advanced undergraduates, graduates, and practicing engineers involved in engineering and computer science"--

"Provides a straightforward, bottom-up approach that assists the reader in obtaining a clear (but theoretically rigorous) understanding of Evolutionary Algorithms, with an emphasis on implementation rather than models"--

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Edition Statements

  • Publication Date:2013.

Publication Statements

  • Publisher(s):Wiley-Blackwell
  • Place of Publication:Chichester
  • Language:eng
  • Publication Date:2013.

The Physical Object

  • Description:1 online resource (1 volume)

Edition Identifiers

  • ISBN:1118659503, 9781118659502
  • oclc:ocn859885568
  • LC Classification:QA76.9.A43
  • Dewey Decimal:006.3

Table of Contents

Cover; Title Page; Copyright Page; SHORT TABLE OF CONTENTS; DETAILED TABLE OF CONTENTS; Acknowledgments; Acronyms; List of Algorithms; PART I INTRODUCTION TO EVOLUTIONARY OPTIMIZATION; 1 Introduction; 1.1 Terminology; 1.2 Why Another Book on Evolutionary Algorithms?; 1.3 Prerequisites; 1.4 Homework Problems; 1.5 Notation; 1.6 Outline of the Book; 1.7 A Course Based on This Book; 2 Optimization; 2.1 Unconstrained Optimization; 2.2 Constrained Optimization; 2.3 Multi-Objective Optimization; 2.4 Multimodal Optimization; 2.5 Combinatorial Optimization; 2.6 Hill Climbing.

2.6.1 Biased Optimization Algorithms2.6.2 The Importance of Monte Carlo Simulations; 2.7 Intelligence; 2.7.1 Adaptation; 2.7.2 Randomness; 2.7.3 Communication; 2.7.4 Feedback; 2.7.5 Exploration and Exploitation; 2.8 Conclusion; Problems; PART II CLASSIC EVOLUTIONARY ALGORITHMS; 3 Genetic Algorithms; 3.1 The History of Genetics; 3.1.1 Charles Darwin; 3.1.2 Gregor Mendel; 3.2 The Science of Genetics; 3.3 The History of Genetic Algorithms; 3.4 A Simple Binary Genetic Algorithm; 3.4.1 A Genetic Algorithm for Robot Design; 3.4.2 Selection and Crossover; 3.4.3 Mutation; 3.4.4 GA Summary.

3.4.5 GA Tuning Parameters and Exa…

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Subjects

Algorithmes ALGORITHMS Calcul naturel Computer algorithms Evolutionary computation Mathematics -- Discrete Mathematics Natural computation Réseaux neuronaux à structure évolutive

Writers

Simon, Dan

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