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Editore: Taylor & Francis Ltd, London, 2025
ISBN 10: 1032070927 ISBN 13: 9781032070926
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EUR 65,05
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Aggiungi al carrelloPaperback. Condizione: new. Paperback. Moth-Flame Optimization algorithm is an emerging meta-heuristic and has been widely used in both science and industry. Solving optimization problem using this algorithm requires addressing a number of challenges, including multiple objectives, constraints, binary decision variables, large-scale search space, dynamic objective function, and noisy parameters.Handbook of Moth-Flame Optimization Algorithm: Variants, Hybrids, Improvements, and Applications provides an in-depth analysis of this algorithm and the existing methods in the literature to cope with such challenges.Key Features:Reviews the literature of the Moth-Flame Optimization algorithmProvides an in-depth analysis of equations, mathematical models, and mechanisms of the Moth-Flame Optimization algorithmProposes different variants of the Moth-Flame Optimization algorithm to solve binary, multi-objective, noisy, dynamic, and combinatorial optimization problemsDemonstrates how to design, develop, and test different hybrids of Moth-Flame Optimization algorithmIntroduces several applications areas of the Moth-Flame Optimization algorithmThis handbook will interest researchers in evolutionary computation and meta-heuristics and those who are interested in applying Moth-Flame Optimization algorithm and swarm intelligence methods overall to different application areas. Moth-Flame Optimization algorithm is an emerging meta-heuristic published in 2015. This book provides in-depth analysis of this algorithm and the existing methods to cope with challenges. It proposes improvements, variants, and hybrids of this algorithm. Applications are also covered to demonstrate the applicability of methods in this book. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Aggiungi al carrelloPaperback. Condizione: Brand New. 346 pages. 9.18x6.12x9.21 inches. In Stock.
Editore: Taylor & Francis Ltd, London, 2025
ISBN 10: 1032070927 ISBN 13: 9781032070926
Lingua: Inglese
Da: AussieBookSeller, Truganina, VIC, Australia
EUR 76,53
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Aggiungi al carrelloPaperback. Condizione: new. Paperback. Moth-Flame Optimization algorithm is an emerging meta-heuristic and has been widely used in both science and industry. Solving optimization problem using this algorithm requires addressing a number of challenges, including multiple objectives, constraints, binary decision variables, large-scale search space, dynamic objective function, and noisy parameters.Handbook of Moth-Flame Optimization Algorithm: Variants, Hybrids, Improvements, and Applications provides an in-depth analysis of this algorithm and the existing methods in the literature to cope with such challenges.Key Features:Reviews the literature of the Moth-Flame Optimization algorithmProvides an in-depth analysis of equations, mathematical models, and mechanisms of the Moth-Flame Optimization algorithmProposes different variants of the Moth-Flame Optimization algorithm to solve binary, multi-objective, noisy, dynamic, and combinatorial optimization problemsDemonstrates how to design, develop, and test different hybrids of Moth-Flame Optimization algorithmIntroduces several applications areas of the Moth-Flame Optimization algorithmThis handbook will interest researchers in evolutionary computation and meta-heuristics and those who are interested in applying Moth-Flame Optimization algorithm and swarm intelligence methods overall to different application areas. Moth-Flame Optimization algorithm is an emerging meta-heuristic published in 2015. This book provides in-depth analysis of this algorithm and the existing methods to cope with challenges. It proposes improvements, variants, and hybrids of this algorithm. Applications are also covered to demonstrate the applicability of methods in this book. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Editore: Taylor & Francis Ltd, London, 2025
ISBN 10: 1032070927 ISBN 13: 9781032070926
Lingua: Inglese
Da: CitiRetail, Stevenage, Regno Unito
EUR 71,77
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Aggiungi al carrelloPaperback. Condizione: new. Paperback. Moth-Flame Optimization algorithm is an emerging meta-heuristic and has been widely used in both science and industry. Solving optimization problem using this algorithm requires addressing a number of challenges, including multiple objectives, constraints, binary decision variables, large-scale search space, dynamic objective function, and noisy parameters.Handbook of Moth-Flame Optimization Algorithm: Variants, Hybrids, Improvements, and Applications provides an in-depth analysis of this algorithm and the existing methods in the literature to cope with such challenges.Key Features:Reviews the literature of the Moth-Flame Optimization algorithmProvides an in-depth analysis of equations, mathematical models, and mechanisms of the Moth-Flame Optimization algorithmProposes different variants of the Moth-Flame Optimization algorithm to solve binary, multi-objective, noisy, dynamic, and combinatorial optimization problemsDemonstrates how to design, develop, and test different hybrids of Moth-Flame Optimization algorithmIntroduces several applications areas of the Moth-Flame Optimization algorithmThis handbook will interest researchers in evolutionary computation and meta-heuristics and those who are interested in applying Moth-Flame Optimization algorithm and swarm intelligence methods overall to different application areas. Moth-Flame Optimization algorithm is an emerging meta-heuristic published in 2015. This book provides in-depth analysis of this algorithm and the existing methods to cope with challenges. It proposes improvements, variants, and hybrids of this algorithm. Applications are also covered to demonstrate the applicability of methods in this book. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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EUR 124,73
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Aggiungi al carrelloPAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.