Handbook of Nature-Inspired Optimization Algorithms: The State of the Art : Volume I: Solving Single Objective Bound-Constrained Real-Parameter Numerical Optimization Problems / / edited by Ali Mohamed, Diego Oliva, Ponnuthurai Nagaratnam Suganthan
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| Titolo: |
Handbook of Nature-Inspired Optimization Algorithms: The State of the Art : Volume I: Solving Single Objective Bound-Constrained Real-Parameter Numerical Optimization Problems / / edited by Ali Mohamed, Diego Oliva, Ponnuthurai Nagaratnam Suganthan
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| Pubblicazione: | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Edizione: | 1st ed. 2022. |
| Descrizione fisica: | 1 online resource (282 pages) |
| Disciplina: | 519.3 |
| 519.6 | |
| Soggetto topico: | Computational intelligence |
| Artificial intelligence | |
| Computational Intelligence | |
| Artificial Intelligence | |
| Persona (resp. second.): | MohamedAli |
| OlivaDiego | |
| NagaratnamPonnuthurai | |
| Nota di contenuto: | 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. |
| Sommario/riassunto: | 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. |
| Titolo autorizzato: | Handbook of Nature-Inspired Optimization Algorithms: The State of the Art |
| ISBN: | 3-031-07512-9 |
| Formato: | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | 9910590081903321 |
| Lo trovi qui: | Univ. Federico II |
| Opac: | Controlla la disponibilità qui |
Serie:
Studies in Systems, Decision and Control, . 2198-4190 ; ; 212