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.
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.
The Moth's Flame is about a woman who fell madly in love with the perfect guy; until he no longer became what the doctor ordered. As time went on her better half began to use drugs and become abusive...
This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and...
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