Handbook of Nature-Inspired Optimization Algorithms: The State of the Art
Volume I: Solving Single Objective Bound-Constrained Real-Parameter Numerical Optimization Problems
1st Edition
Published on 31. August 2022
X, 279 pages
978-3-031-07512-4 (ISBN)
Description
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.More details
Other editions
Additional editions
Ali Mohamed | Diego Oliva | Ponnuthurai Nagaratnam Suganthan
Handbook of Nature-Inspired Optimization Algorithms: The State of the Art
Volume I: Solving Single Objective Bound-Constrained Real-Parameter Numerical Optimization Problems
Book
09/2022
Springer
€160.49
Shipment within 15-20 days
Content
Chaotic-SCA Salp Swarm Algorithm Enhanced with Opposition Based Learning: Application to Decrease Carbon Footprint in Patient Flow.- Design and Performance Evaluation of Objective Functions Based on Various Measures of Fuzzy Entropies for Image Segmentation using Grey Wolf Optimization.- Improved Artificial Bee Colony Algorithm with Adaptive Pursuit Based Strategy Selection.- Beetle Antennae Search Algorithm for the Motion Planning of Industrial Manipulator.- Solving Optimal Power Flow with Considering Placement of TCSC and FACTS Cost Using Cuckoo Search Algorithm.
