원문정보
초록
영어
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.
목차
1. Introduction
2. Related works
2.1. Standard PSO
2.2. Harmony search
3. The realization of IPSO based of HS
4. Simulation results and comparisons
4.1. Experimental parameters setting
4.2. Test functions
4.3. Experimental results
5. Conclusions
Refrenece: