An Improved PSO-based of Harmony Search for Complicated Optimization Problems

As an optimization technique, particle swarm optimization (PSO) has obtained much attention during the past decade. It is gaining popularity, especially because of the speed of convergence and the fact that it is easy to realize. To enhance the performance of PSO, an improved hybrid particle swarm optimization (IPSO) is proposed to solve complex optimization problems more efficiently, accurately and reliably. It provides a new way of producing new individuals through organically merges the harmony search (HS) method into particle swarm optimization (PSO). During the course of evolvement, harmony search is used to generate new solutions and this makes IPSO algorithm have more powerful exploitation capabilities. Simulation results and comparisons with the standard PSO based on several well-studied benchmarks demonstrate that the IPSO can effectively enhance the searching efficiency and greatly improve the search quality.