Genetic Algorithm, Particle Swarm Optimization and Harmony Search: A quick comparison

There exists several complex optimization problems, are difficult to solve using simple conventional or mathematical approach. Many scientific applications have a search space exponentially proportional to the problem dimensions, cannot be solved employing exhaustive search methods. Therefore, there is considerable interest in metaheuristic methods attempt to discover near optimal solution within the acceptable time. This paper presents a comprehensive study and comparison of three: Genetic Algorithm, Particle Swarm Optimization and Harmony Search, global optimization algorithms. The comparative analysis has been reported in an organized manner for quick review. The underlying motivation is to identify possibility to develop a new hybrid algorithm to solve real world problems.