Distributed Multi-objective Particle Swarm Optimization using Time-delayed Virtual Global Best Method

Yuji Sato, Shota Ueno, Toshio Hirotsu

2019

Abstract

To reduce the computational cost of particle swarm optimization (PSO) methods, research has begun on the use of Graphics Processing Units (GPUs) to achieve faster processing speeds. However, since PSO methods search based on a global best value, they are hampered by the frequent need for communication with global memory. Even using a standard PSO that uses a local best value does not solve this problem. In this paper, we propose a virtual global best method that speeds up computations by defining a time-delayed global best as a virtual global best in order to reduce the frequency of communication with low-speed global memory. We also propose a method that combines decomposition-based multi-objective PSO (MOPSO/D) with a virtual global best method to speed up multi-objective particle swarm optimization by running it in parallel while maintaining search accuracy, and we demonstrate the effectiveness of this approach by using a number of unimodal/multimodal single objective benchmark test functions and three classical benchmark test functions with two objectives.

Paper Citation

in Harvard Style

Sato Y., Ueno S. and Hirotsu T. (2019). Distributed Multi-objective Particle Swarm Optimization using Time-delayed Virtual Global Best Method. In Proceedings of the 11th International Joint Conference on Computational Intelligence (IJCCI 2019) - Volume 1: ECTA; ISBN 978-989-758-384-1, SciTePress, pages 21-30. DOI: 10.5220/0007955200210030

in Bibtex Style

@conference{ecta19,
author={Yuji Sato and Shota Ueno and Toshio Hirotsu},
title={Distributed Multi-objective Particle Swarm Optimization using Time-delayed Virtual Global Best Method},
booktitle={Proceedings of the 11th International Joint Conference on Computational Intelligence (IJCCI 2019) - Volume 1: ECTA},
year={2019},
pages={21-30},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007955200210030},
isbn={978-989-758-384-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Computational Intelligence (IJCCI 2019) - Volume 1: ECTA
TI - Distributed Multi-objective Particle Swarm Optimization using Time-delayed Virtual Global Best Method
SN - 978-989-758-384-1
AU - Sato Y.
AU - Ueno S.
AU - Hirotsu T.
PY - 2019
SP - 21
EP - 30
DO - 10.5220/0007955200210030
PB - SciTePress