Handbook moth flame optimization algorithm (32 résultats)

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Taschenbuch. Etat : Neu. Handbook of Moth-Flame Optimization Algorithm | Variants, Hybrids, Improvements, and Applications | Seyedali Mirjalili | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2025 | CRC Press | EAN 9781032070926 | Verantwortliche Person für die EU: Taylor & Francis Verlag GmbH, Kaufingerstr. 24, 80331 München, gpsr[at]taylorandfrancis[dot]com | Anbieter: preigu.…

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 348 pp. Englisch.…

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.…

Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Seyedali Mirjalili is a Professor at Torrens University Center for Artificial Intelligence Research and Optimization and internationally recognized for his advances in nature-inspired Artificial Intelligence (AI) techniques. He is the au.…

Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 algorithm Provides an in-depth analysis of equations, mathematical models, and mechanisms of the Moth-Flame Optimization algorithm Proposes different variants of the Moth-Flame Optimization algorithm to solve binary, multi-objective, noisy, dynamic, and combinatorial optimization problems Demonstrates how to design, develop, and test different hybrids of Moth-Flame Optimization algorithm Introduces several applications areas of the Moth-Flame Optimization algorithm This 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. 348 pp. Englisch. …

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