Handbook of moth flame optimization algorithm : variants hybrids improvements and applications 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