MATLAB Genetic Algorithm Toolbox and Its Applications

This article introduces a companion Genetic Algorithm Toolbox called gatbx, which is associated with MATLAB Genetic Algorithm Toolbox and Applications. This toolbox enables implementation of various genetic algorithm applications and functionalities. It provides a comprehensive suite of tools and functions that facilitate easier development and experimentation with genetic algorithms. Key functions in the toolbox include population initialization, fitness evaluation, selection operations, crossover methods (such as single-point and uniform crossover), mutation operators, and termination criteria checking. Through this toolbox, users can efficiently solve diverse optimization and search problems using genetic algorithm techniques. The implementation follows standard genetic algorithm workflow: generating initial population, evaluating fitness, selecting parents, applying genetic operators, and iterating until convergence. Therefore, this companion Genetic Algorithm Toolbox serves as a valuable resource that is essential for researchers and practitioners working with genetic algorithms.