Handbook of Nature-Inspired Optimization Algorithms: The State of the Art
Springer International Publishing (Verlag)
978-3-031-07514-8 (ISBN)
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.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.
| Erscheinungsdatum | 03.09.2023 |
|---|---|
| Reihe/Serie | Studies in Systems, Decision and Control |
| Zusatzinfo | X, 279 p. 94 illus., 73 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 450 g |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Technik | |
| Schlagworte | evolutionary algorithms • Metaheuristics • Nature-Inspired Optimization Algorithms • NIOAs • Optimization |
| ISBN-10 | 3-031-07514-5 / 3031075145 |
| ISBN-13 | 978-3-031-07514-8 / 9783031075148 |
| Zustand | Neuware |
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