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010 a| 2022014422;

020 a| 9781032070919q| (hbk);

020 a| 9781032070926q| (pbk);

020 z| 9781003205326q| (ebk);

035 a| (WaSeSS)ssj0002689871;

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245 00 a| Handbook of moth-flame optimization algorithmh| [electronic resource] :b| variants, hybrids, improvements, and applications /c| edited by Seyedali Mirjalili.;

250 a| First edition.;

260 a| Boca Raton :b| CRC Press,c| [2023];

263 a| 2209;

300 a| pages cm.;

490 0 a| Advances in metaheurists;

500 a| Includes index.;

506 a| Available only to authorized users.;

520 a| "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, noisy parameters, just to name a few. 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, meta-heuristics and to those who are interested in applying Moth-Flame Optimization algorithm and swarm intelligence methods overall to different application areas"--c| Provided by publisher.;

538 a| Mode of access: World Wide Web;

650 0 a| Nature-inspired algorithms.=| ^A1480146;

650 0 a| Artificial intelligence.=| ^A15394;

655 0 a| Electronic books.=| ^A491897;

700 1 a| Mirjalili, Seyedali.?| UNAUTHORIZED;

856 40 z| Full text available from Taylor & Francis eBooksu| https://go.openathens.net/redirector/ecu.edu?url=https%3A%2F%2Fwww.taylorfrancis.com%2Fbooks%2F9781003205326;

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Handbook of moth-flame optimization algorithm variants, hybrids, improvements, and applications / edited by Seyedali Mirjalili.

Other author	Mirjalili, Seyedali.
Format	Electronic
Edition	First edition.
Publication Info	Boca Raton : CRC Press, [2023]
Description	pages cm.
Supplemental Content	Full text available from Taylor & Francis eBooks
Subjects	Nature-inspired algorithms. Artificial intelligence.

Series	Advances in metaheurists
Abstract	"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, noisy parameters, just to name a few. 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, meta-heuristics and to those who are interested in applying Moth-Flame Optimization algorithm and swarm intelligence methods overall to different application areas"-- Provided by publisher.
General note	Includes index.
Access restriction	Available only to authorized users.
Technical details	Mode of access: World Wide Web
Genre/form	Electronic books.
LCCN	2022014422
ISBN	9781032070919 (hbk)
ISBN	9781032070926 (pbk)
ISBN	(ebk)

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Handbook of moth-flame optimization algorithm variants, hybrids, improvements, and applications / edited by Seyedali Mirjalili.

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