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Handbook of Nature-Inspired Optimization Algorithms: The State of the Art
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Handbook of Nature-Inspired Optimization Algorithms: The State of the Art : Volume I: Solving Single Objective Bound-Constrained Real-Parameter Numerical Optimization Problems

2022 ed.

Book Details

Format Hardback or Cased Book
ISBN-10 3031075110
ISBN-13 9783031075117
Edition 2022 ed.
Publisher Springer International Publishing AG
Imprint Springer International Publishing AG
Country of Manufacture GB
Country of Publication GB
Publication Date Sep 1st, 2022
Print length 279 Pages
Product Classification: Artificial intelligence
Ksh 23,400.00
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The introduction of nature-inspired optimization algorithms (NIOAs), over the past three decades, helped solve nonlinear, high-dimensional, and complex computational optimization problems. NIOAs have been originally developed to overcome the challenges of global optimization problems such as nonlinearity, non-convexity, non-continuity, non-differentiability, and/or multimodality which traditional numerical optimization techniques had difficulties solving. The main objective for this book is to make available a self-contained collection of modern research addressing the general bound-constrained optimization problems in many real-world applications using nature-inspired optimization algorithms. This book is suitable for a graduate class on optimization, but will also be useful for interested senior students working on their research projects.

The introduction of nature-inspired optimization algorithms (NIOAs), over the past three decades, helped solve nonlinear, high-dimensional, and complex computational optimization problems. NIOAs have been originally developed to overcome the challenges of global optimization problems such as nonlinearity, non-convexity, non-continuity, non-differentiability, and/or multimodality which traditional numerical optimization techniques had difficulties solving.

The main objective for this book is to make available a self-contained collection of modern research addressing the general bound-constrained optimization problems in many real-world applications using nature-inspired optimization algorithms. This book is suitable for a graduate class on optimization, but will also be useful for interested senior students working on their research projects.

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