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Nature-Inspired Metaheuristic Algorithms for Engineering Optimization Applications (Springer Tracts in Nature-Inspired Computing) - Tapa dura

 
9789813367722: Nature-Inspired Metaheuristic Algorithms for Engineering Optimization Applications (Springer Tracts in Nature-Inspired Computing)

Sinopsis

This book engages in an ongoing topic, such as the implementation of nature-inspired metaheuristic algorithms, with a main concentration on optimization problems in different fields of engineering optimization applications. The chapters of the book provide concise overviews of various nature-inspired metaheuristic algorithms, defining their profits in obtaining the optimal solutions of tiresome engineering design problems that cannot be efficiently resolved via conventional mathematical-based techniques. Thus, the chapters report on advanced studies on the applications of not only the traditional, but also the contemporary certain nature-inspired metaheuristic algorithms to specific engineering optimization problems with single and multi-objectives. Harmony search, artificial bee colony, teaching learning-based optimization, electrostatic discharge, grasshopper, backtracking search, and interactive search are just some of the methods exhibited and consulted step by step in application contexts. The book is a perfect guide for graduate students, researchers, academicians, and professionals willing to use metaheuristic algorithms in engineering optimization applications.

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Acerca del autor

Serdar Carbas received his B.Sc. in the Department of Civil Engineering from Ataturk University, Erzurum, Turkey, and his M.Sc. and Ph.D. in the Department of Engineering Sciences from Middle East Technical University (METU), Ankara, Turkey. He was  Visiting Scholar at the University of California, Los Angeles (UCLA), CA, USA (August 2011–September 2012). His current research fields cover the use of metaheuristic optimization techniques that are found quite effective in obtaining the solution of combinatorial optimization problems which are based on natural phenomena in the field of optimum design of structures. He has authored several book chapters and published more than 40 peer-reviewed research papers. He is Associate Professor at the Department of Civil Engineering in Karamanoglu Mehmetbey University, Karaman, Turkey. Also, he is Adjunct Associate Professor at the Civil Engineering Department of KTO Karatay University, Konya, Turkey.

Abdurrahim Toktas is Associate Professor at the Department of Electrical and Electronics Engineering, Karamanoglu Mehmetbey University, Karaman, Turkey. He received B.Sc. degree in Electrical and Electronics Engineering at Gaziantep University, Gaziantep, Turkey, in July 2002. He worked as Telecom Expert from November 2003 to December 2009 for Turk Telecom Company which is the national PSTN and wideband Internet operator. He received M.Sc. and Ph.D. degrees in Electrical and Electronics Engineering at Mersin University, Mersin, Turkey, in January 2010 and July 2014, respectively. He worked as Network Expert in the Department of Information Technologies at Mersin University from December 2009 to January 2015. He is an editorial board member of the Journal of Recent Advances in Electrical & Electronic Engineering. He is the author of more than ninety research items involving articles, conference proceedings, and projects. His current research interests include electromagnetic modelling, computational electromagnetics, microstrip/printed antenna designing, radar absorber material modelling, design of MIMO antennas, design of UWB antennas, optimization algorithms, machine learnings, and surrogate model.

Deniz Ustun received his B.Sc. degree from the Department of Computer Science Engineering, Istanbul University, Istanbul, Turkey, in 2001. Besides, he received his M.Sc. and Ph.D. degrees from the Department of Electrical and Electronics Engineering, Mersin University, Mersin, Turkey, in 2009 and 2017, respectively. From 2003 to 2017, he was a senior lecturer in the Department of Software Engineering, Mersin University, Mersin, Turkey. Formerly, he was Assistant Professor in the Department of Computer Engineering, Karamanoglu Mehmetbey University, Karaman, Turkey, between 2017 and 2020. He has been working for the Department of Computer Engineering, Tarsus University, Tarsus, Turkey, since March 2020, as Assistant Professor. His current research interests include heuristic and artificial intelligence-based optimization algorithms, surrogate models, machine learning, microstrip antennas, and so forth.

De la contraportada

This book engages in an ongoing topic, such as the implementation of nature-inspired metaheuristic algorithms, with a main concentration on optimization problems in different fields of engineering optimization applications. The chapters of the book provide concise overviews of various nature-inspired metaheuristic algorithms, defining their profits in obtaining the optimal solutions of tiresome engineering design problems that cannot be efficiently resolved via conventional mathematical-based techniques. Thus, the chapters report on advanced studies on the applications of not only the traditional, but also the contemporary certain nature-inspired metaheuristic algorithms to specific engineering optimization problems with single and multi-objectives. Harmony search, artificial bee colony, teaching learning-based optimization, electrostatic discharge, grasshopper, backtracking search, and interactive search are just some of the methods exhibited and consulted step by step in application contexts. The book is a perfect guide for graduate students, researchers, academicians, and professionals willing to use metaheuristic algorithms in engineering optimization applications.

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9789813367753: Nature-Inspired Metaheuristic Algorithms for Engineering Optimization Applications (Springer Tracts in Nature-Inspired Computing)

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ISBN 10:  981336775X ISBN 13:  9789813367753
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Carbas, S. et al. (Eds.)
Publicado por Singapore, Springer Singapore., 2021
ISBN 10: 9813367725 ISBN 13: 9789813367722
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1st ed. 2021. XII, 404 p. Hardcover. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch. Nº de ref. del artículo: 326NB

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Carbas, Serdar|Toktas, Abdurrahim|Ustun, Deniz
Publicado por Springer Singapore, 2021
ISBN 10: 9813367725 ISBN 13: 9789813367722
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Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents concise overviews of various nature-inspired metaheuristic algorithmsProvides solutions to specific engineering optimization problems with single and multi-objectivesServes as a reference for. Nº de ref. del artículo: 437752874

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Publicado por Springer, 2021
ISBN 10: 9813367725 ISBN 13: 9789813367722
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Serdar Carbas
ISBN 10: 9813367725 ISBN 13: 9789813367722
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book engages in an ongoing topic, such as the implementation of nature-inspired metaheuristic algorithms, with a main concentration on optimization problems in different fields of engineering optimization applications. The chapters of the book provide concise overviews of various nature-inspired metaheuristic algorithms, defining their profits in obtaining the optimal solutions of tiresome engineering design problems that cannot be efficiently resolved via conventional mathematical-based techniques. Thus, the chapters report on advanced studies on the applications of not only the traditional, but also the contemporary certain nature-inspired metaheuristic algorithms to specific engineering optimization problems with single and multi-objectives. Harmony search, artificial bee colony, teaching learning-based optimization, electrostatic discharge, grasshopper, backtracking search, and interactive search are just some of the methods exhibited and consulted step by step in applicationcontexts. The book is a perfect guide for graduate students, researchers, academicians, and professionals willing to use metaheuristic algorithms in engineering optimization applications. 428 pp. Englisch. Nº de ref. del artículo: 9789813367722

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Serdar Carbas
ISBN 10: 9813367725 ISBN 13: 9789813367722
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book engages in an ongoing topic, such as the implementation of nature-inspired metaheuristic algorithms, with a main concentration on optimization problems in different fields of engineering optimization applications. The chapters of the book provide concise overviews of various nature-inspired metaheuristic algorithms, defining their profits in obtaining the optimal solutions of tiresome engineering design problems that cannot be efficiently resolved via conventional mathematical-based techniques. Thus, the chapters report on advanced studies on the applications of not only the traditional, but also the contemporary certain nature-inspired metaheuristic algorithms to specific engineering optimization problems with single and multi-objectives. Harmony search, artificial bee colony, teaching learning-based optimization, electrostatic discharge, grasshopper, backtracking search, and interactive search are just some of the methods exhibited and consulted step by step in applicationcontexts. The book is a perfect guide for graduate students, researchers, academicians, and professionals willing to use metaheuristic algorithms in engineering optimization applications. Nº de ref. del artículo: 9789813367722

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Serdar Carbas
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Buch. Condición: Neu. Neuware -This book engages in an ongoing topic, such as the implementation of nature-inspired metaheuristic algorithms, with a main concentration on optimization problems in different fields of engineering optimization applications. The chapters of the book provide concise overviews of various nature-inspired metaheuristic algorithms, defining their profits in obtaining the optimal solutions of tiresome engineering design problems that cannot be efficiently resolved via conventional mathematical-based techniques. Thus, the chapters report on advanced studies on the applications of not only the traditional, but also the contemporary certain nature-inspired metaheuristic algorithms to specific engineering optimization problems with single and multi-objectives. Harmony search, artificial bee colony, teaching learning-based optimization, electrostatic discharge, grasshopper, backtracking search, and interactive search are just some of the methods exhibited and consulted step by step in applicationcontexts. The book is a perfect guide for graduate students, researchers, academicians, and professionals willing to use metaheuristic algorithms in engineering optimization applications.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 428 pp. Englisch. Nº de ref. del artículo: 9789813367722

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