Handbook of Moth-Flame Optimization Algorithm Variants Hybrids Improvements and Applications

Description

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. | Handbook of Moth-Flame Optimization Algorithm Variants Hybrids Improvements and Applications