- 期刊
Hierarchical Particle Swarm Optimization for Optimization Problems
並列摘要
In this paper, a hierarchical particle swarm optimization (HPSO) is proposed to improve the premature convergence in the PSO approach. In the proposed HPSO approach, all particles are arranged in a regular tree structure and move up or down in the tree based on their fitness value. For the velocity update of each particle, it depends on the position of each particle in the tree. Besides, a mutation operator is added into the proposed HPSO approach. Consequently, the diversity of the population increases so that the HPSO approach can improve the premature convergence in the PSO approach. Finally, several benchmark functions for optimization problems are utilized to illustrate the effectiveness of the proposed HPSO approach to improving the premature convergence.
延伸閱讀
- 李維平、江正文（2007）。Improving the Performance of Particle Swarm Optimization Algorithms with Activation Strategy。先進工程學刊，2(4)，283-293。https://doi.org/10.29948/JAE.200710.0014
- BUI, T., NGUYEN, T., VO, B., NGUYEN, T., PEDRYCZ, W., & SNASEL, V. (2018). Application of Particle Swarm Optimization to Create Multiple-Choice Tests. Journal of Information Science and Engineering, 34(6), 1405-1423. https://doi.org/10.6688/JISE.201811_34(6).0004
- Chang, J. F., Chu, S. C., Roddick, J. F., & Pan, J. S. (2005). A Parallel Particle Swarm Optimization Algorithm with Communication Strategies. Journal of Information Science and Engineering, 21(4), 809-818. https://doi.org/10.6688/JISE.2005.21.4.6
- Maheshkumar, Y., Ravi, V., & Abraham, A. (2013). A PARTICLE SWARM OPTIMIZATION-THRESHOLD ACCEPTING HYBRID ALGORITHM FOR UNCONSTRAINED OPTIMIZATION. Neural Network World, 23(3), 191-221. https://doi.org/10.14311/NNW.2013.23.013
- Jamian, J. J., Abdullah, M. N., Mokhlis, H., Mustafa, M. W., & Bakar, A. H. A. (2014). Global Particle Swarm Optimization for High Dimension Numerical Functions Analysis. Journal of Applied Mathematics, 2014(), 688-701-275. https://doi.org/10.1155/2014/329193