Particle Swarm Optimization Algorithm Based on Artificial Potential Field

DOI

10.2991/mecae-18.2018.104How to use a DOI?

Keywords

Particle swarm optimization, artificial potential field

Abstract

Artificial potential field method is a simple and effective path planning algorithm. In this paper, the basic idea of artificial potential field method is inherited. The gravitational potential field and repulsive potential field are introduced into particle swarm optimization. The gravitational potential field is used to enhance the optimization of particles. The repulsive potential field is used to increase the search range of particles to prevent the particles from falling into the local excellent solution. This paper tests the function, experiments show that this method is effective.

Copyright

© 2018, 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  - Dianna Song
AU  - Jianhua Qu
PY  - 2018/03
DA  - 2018/03
TI  - Particle Swarm Optimization Algorithm Based on Artificial Potential Field
BT  - Proceedings of the 2018 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2018)
PB  - Atlantis Press
SP  - 444
EP  - 447
SN  - 2352-5401
UR  - https://doi.org/10.2991/mecae-18.2018.104
DO  - 10.2991/mecae-18.2018.104
ID  - Song2018/03
ER  -