Handbook Of Nature-inspired Optimization

Mohamed, Ali

ISBN 10: 3031075110 ISBN 13: 9783031075117

Edit� par Springer, 2022

Neuf(s) Couverture rigide

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Synopsis :

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.

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Titre : Handbook Of Nature-inspired Optimization
�diteur : Springer
Date d'�dition : 2022
Reliure : Couverture rigide
Etat : New

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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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Edit� par Palgrave Macmillan, 2022

ISBN 10 : 3031075110 ISBN 13 : 9783031075117

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Etat : Hervorragend. Zustand: Hervorragend | Seiten: 292 | Sprache: Englisch | Produktart: B�cher | 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. N� de r�f. du vendeur 40274856/1

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Handbook of Nature-Inspired Optimization Algorithms: The State of the Art (eng)

Mohamed, Ali

Edit� par Springer, 2022

ISBN 10 : 3031075110 ISBN 13 : 9783031075117

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Handbook of Nature-Inspired Optimization Algorithms: The State of the Art

Edit� par Springer, Berlin|Springer International Publishing|Springer, 2022

ISBN 10 : 3031075110 ISBN 13 : 9783031075117

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Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 o. N� de r�f. du vendeur 585900177

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Handbook of Nature-Inspired Optimization Algorithms: The State of the Art

Ali Mohamed

Edit� par Springer International Publishing Sep 2022, 2022

ISBN 10 : 3031075110 ISBN 13 : 9783031075117

Neuf Couverture rigide

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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne

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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 292 pp. Englisch. N� de r�f. du vendeur 9783031075117

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Handbook of Nature-Inspired Optimization Algorithms: The State of the Art

Ali Mohamed

Edit� par Springer, Springer Sep 2022, 2022

ISBN 10 : 3031075110 ISBN 13 : 9783031075117

Neuf Couverture rigide

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Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne

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Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 292 pp. Englisch. N� de r�f. du vendeur 9783031075117

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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

Edit� par Springer International Publishing, 2022

ISBN 10 : 3031075110 ISBN 13 : 9783031075117

Neuf Couverture rigide

Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Buch. Etat : Neu. 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. N� de r�f. du vendeur 9783031075117

Contacter le vendeur