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

Ali Mohamed

ISBN 10: 3031075145 / ISBN 13: 9783031075148

Published by Springer International Publishing, 2023

About this Item

Druck auf Anfrage Neuware - Printed after ordering - 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.

Seller Inventory # 9783031075148

Bibliographic Details

• Title: Handbook of Nature-Inspired Optimization Algorithms: The State of the Art : Volume I: Solving Single Objective Bound-Constrained Real-Parameter Numerical Optimization Problems
• Publisher: Springer International Publishing
• Publication Date: 2023
• Language: English
• ISBN 10: 3031075145
• ISBN 13: 9783031075148
• Binding: Taschenbuch
• Condition: Neu

About this title

Synopsis

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.