Study on the Strategy of Acceleration Factor in Particle Swarm Optimization Algorithm

DOI

10.2991/ccit-14.2014.95How to use a DOI?

Keywords

particle swarm optimization, acceleration factor, dynamic adjustment factor

Abstract

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.

Copyright

© 2014, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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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  - Proceedings of the 2014 International Conference on Computer, Communications and Information Technology
PB  - Atlantis Press
SP  - 370
EP  - 373
SN  - 1951-6851
UR  - https://doi.org/10.2991/ccit-14.2014.95
DO  - 10.2991/ccit-14.2014.95
ID  - Li2014/01
ER  -