- 期刊
- OpenAccess
A Parallel Particle Swarm Optimization Algorithm with Communication Strategies
並列摘要
Particle swarm optimization (PSO) is an alternative population-based evolutionary computation technique. It has been shown to be capable of optimizing hard mathematical problems in continuous or binary space. We present here a parallel version of the particle swarm optimization (PPSO) algorithm together with three communication strategies which can be used according to the independence of the data. The first strategy is designed for solution parameters that are independent or are only loosely correlated, such as the Rosenbrock and Rastrigrin functions. The second communication strategy can be applied to parameters that are more strongly correlated such as the Griewank function. In cases where the properties of the parameters are unknown, a third hybrid communication strategy can be used. Experimental results demonstrate the usefulness of the proposed PPSO algorithm.
延伸閱讀
- 李維平、王雅賢、江正文（2008）。Research on a Modified Particle Swarm Optimization Algorithm。科學與工程技術期刊，4(2)，51-62。https://doi.org/10.7117/JSET.200806.0051
- 呂政儒（2023）。An Improved Particle Swarm Optimization Algorithm for Feature Selection in Classification〔碩士論文，國立臺灣師範大學〕。華藝線上圖書館。https://doi.org/10.6345/NTNU202300219
- Kuo, H. C., Chang, J. R., & Liu, C. H. (2006). Particle Swarm Optimization for Global Optimization Problems. Journal of Marine Science and Technology, 14(3), 170-181. https://doi.org/10.6119/JMST.200609_14(3).0006
- Li, N. J. (2015). Weighted Particle Based Modified Particle Swarm Optimization and Its Applications [doctoral dissertation, National Central University]. Airiti Library. https://www.airitilibrary.com/Article/Detail?DocID=U0031-0412201512071910
- 廖雲枝、李維平、賀嘉生、江正文（2009）。Improving the Performance of Particle Swarm Optimization Algorithms with Diversity-Based Activation Strategy。先進工程學刊，4(4)，417-421。https://doi.org/10.29948/JAE.200910.0016