Handbook of Whale Optimization Algorithm: Variants, Hybrids, Improvements, and Applications provides the most in-depth look at an emerging meta-heuristic that has been widely used in both science and industry. Whale Optimization Algorithm has been cited more than 5000 times in Google Scholar, thus solving optimization problems 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 to name a few. This handbook provides readers with in-depth analysis of this algorithm and existing methods in the literature to cope with such challenges.The authors and editors also propose several improvements, variants and hybrids of this algorithm. Several applications are also covered to demonstrate the applicability of methods in this book.- Provides in-depth analysis of equations, mathematical models and mechanisms of the Whale Optimization Algorithm- Proposes different variants of the Whale Optimization Algorithm to solve binary, multiobjective, noisy, dynamic and combinatorial optimization problems- Demonstrates how to design, develop and test different hybrids of Whale Optimization Algorithm- Introduces several application areas of the Whale Optimization Algorithm, focusing on sustainability- Includes source code from applications and algorithms that is available online

Handbook of Whale Optimization Algorithm: Variants, Hybrids, Improvements, and Applications provides the most in-depth look at an emerging meta-heuristic that has been widely used in both science and industry. Whale Optimization Algorithm has been cited more than 5000 times in Google Scholar, thus solving optimization problems 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 to name a few. This handbook provides readers with in-depth analysis of this algorithm and existing methods in the literature to cope with such challenges.The authors and editors also propose several improvements, variants and hybrids of this algorithm. Several applications are also covered to demonstrate the applicability of methods in this book.- Provides in-depth analysis of equations, mathematical models and mechanisms of the Whale Optimization Algorithm- Proposes different variants of the Whale Optimization Algorithm to solve binary, multiobjective, noisy, dynamic and combinatorial optimization problems- Demonstrates how to design, develop and test different hybrids of Whale Optimization Algorithm- Introduces several application areas of the Whale Optimization Algorithm, focusing on sustainability- Includes source code from applications and algorithms that is available online