Introduction to Nature-Inspired Optimization

Nonfiction, Science & Nature, Mathematics, Applied
Cover of the book Introduction to Nature-Inspired Optimization by George Lindfield, John Penny, Elsevier Science
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Author: George Lindfield, John Penny ISBN: 9780128036662
Publisher: Elsevier Science Publication: August 10, 2017
Imprint: Academic Press Language: English
Author: George Lindfield, John Penny
ISBN: 9780128036662
Publisher: Elsevier Science
Publication: August 10, 2017
Imprint: Academic Press
Language: English

Introduction to Nature-Inspired Optimization brings together many of the innovative mathematical methods for non-linear optimization that have their origins in the way various species behave in order to optimize their chances of survival. The book describes each method, examines their strengths and weaknesses, and where appropriate, provides the MATLAB code to give practical insight into the detailed structure of these methods and how they work.

Nature-inspired algorithms emulate processes that are found in the natural world, spurring interest for optimization. Lindfield/Penny provide concise coverage to all the major algorithms, including genetic algorithms, artificial bee colony algorithms, ant colony optimization and the cuckoo search algorithm, among others. This book provides a quick reference to practicing engineers, researchers and graduate students who work in the field of optimization.

  • Applies concepts in nature and biology to develop new algorithms for nonlinear optimization
  • Offers working MATLABĀ® programs for the major algorithms described, applying them to a range of problems
  • Provides useful comparative studies of the algorithms, highlighting their strengths and weaknesses
  • Discusses the current state-of-the-field and indicates possible areas of future development
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Introduction to Nature-Inspired Optimization brings together many of the innovative mathematical methods for non-linear optimization that have their origins in the way various species behave in order to optimize their chances of survival. The book describes each method, examines their strengths and weaknesses, and where appropriate, provides the MATLAB code to give practical insight into the detailed structure of these methods and how they work.

Nature-inspired algorithms emulate processes that are found in the natural world, spurring interest for optimization. Lindfield/Penny provide concise coverage to all the major algorithms, including genetic algorithms, artificial bee colony algorithms, ant colony optimization and the cuckoo search algorithm, among others. This book provides a quick reference to practicing engineers, researchers and graduate students who work in the field of optimization.

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