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 ...
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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.
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New. Trade paperback (US). Glued binding. 332 p. Contains: Unspecified, Illustrations, black & white, Illustrations, color, Halftones, black & white, Halftones, color, Line drawings, black & white, Line drawings, color. Advances in Metaheuristics.
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New. Print on demand Trade paperback (US). Glued binding. 332 p. Contains: Unspecified, Illustrations, black & white, Illustrations, color, Halftones, black & white, Halftones, color, Line drawings, black & white, Line drawings, color. Advances in Metaheuristics.
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Fine. Trade paperback (US). Glued binding. 332 p. Contains: Unspecified, Illustrations, black & white, Illustrations, color, Halftones, black & white, Halftones, color, Line drawings, black & white, Line drawings, color. Advances in Metaheuristics. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers.
Add this copy of Handbook of Moth-Flame Optimization Algorithm: Variants to cart. $69.81, new condition, Sold by GreatBookPricesUK5 rated 4.0 out of 5 stars, ships from Castle Donington, DERBYSHIRE, UNITED KINGDOM, published 2025 by CRC Press.
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New. Trade paperback (US). Glued binding. 332 p. Contains: Unspecified, Illustrations, black & white, Illustrations, color, Halftones, black & white, Halftones, color, Line drawings, black & white, Line drawings, color. Advances in Metaheuristics. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers.
