Handbook of Nature-Inspired Optimization Algorithms: The State of the Art
Volume I: Solving Single Objective Bound-Constrained Real-Parameter Numerical Optimization Problems
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Beschreibung
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.Explains the algorithms used, selected problems, and the implementation Focuses on solving single objective bound-constrained real parameter numerical optimization problems with NIOAs Provides practical examples, comparisons, and experimental results
Autor*in
Ali Mohamed
Themen in »Handbook of Nature-Inspired Optimization Algorithms: The State of the Art«
Nature-Inspired Optimization Algorithms NIOAs Optimization Metaheuristics Evolutionary Algorithms