Study on the Strategy of Acceleration Factor in Particle Swarm Optimization Algorithm
Zhe Li, Peng Bai, R.-L. Tan, Y.-B. Shang, J.-J. Wang
Available Online January 2014.
- https://doi.org/10.2991/ccit-14.2014.95How to use a DOI?
- particle swarm optimization, acceleration factor, dynamic adjustment factor
- Concerning the problem of Particle swarm optimization for solving complex multimodal function could easily fall into premature convergence, this paper proposed an algorithm of dynamically changing acceleration factor particle swarm optimization (CAPSO). According to the motion characteristics of the particles at different stages, acceleration factor of the particle velocity update formula were constructed as a monotonically increasing function and monotonically decreasing function. By setting the dynamic adjustment factor to dynamically determine the acceleration factor expression based on the actual simulation conditions, the algorithm had a better ability to adapt. Validated through four standard test functions and compared with other similar algorithms, numerical simulation results show that by adjusting the dynamic acceleration factor the proposed algorithm had better optimization precision and execution ability compared with other algorithms.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Zhe Li AU - Peng Bai AU - R.-L. Tan AU - Y.-B. Shang AU - J.-J. Wang PY - 2014/01 DA - 2014/01 TI - Study on the Strategy of Acceleration Factor in Particle Swarm Optimization Algorithm BT - 2014 International Conference on Computer, Communications and Information Technology (CCIT 2014) PB - Atlantis Press SN - 1951-6851 UR - https://doi.org/10.2991/ccit-14.2014.95 DO - https://doi.org/10.2991/ccit-14.2014.95 ID - Li2014/01 ER -